WorldWideScience

Sample records for computational cell biology

  1. Computational Tools for Stem Cell Biology.

    Science.gov (United States)

    Bian, Qin; Cahan, Patrick

    2016-12-01

    For over half a century, the field of developmental biology has leveraged computation to explore mechanisms of developmental processes. More recently, computational approaches have been critical in the translation of high throughput data into knowledge of both developmental and stem cell biology. In the past several years, a new subdiscipline of computational stem cell biology has emerged that synthesizes the modeling of systems-level aspects of stem cells with high-throughput molecular data. In this review, we provide an overview of this new field and pay particular attention to the impact that single cell transcriptomics is expected to have on our understanding of development and our ability to engineer cell fate. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. The Virtual Cell: a software environment for computational cell biology.

    Science.gov (United States)

    Loew, L M; Schaff, J C

    2001-10-01

    The newly emerging field of computational cell biology requires software tools that address the needs of a broad community of scientists. Cell biological processes are controlled by an interacting set of biochemical and electrophysiological events that are distributed within complex cellular structures. Computational modeling is familiar to researchers in fields such as molecular structure, neurobiology and metabolic pathway engineering, and is rapidly emerging in the area of gene expression. Although some of these established modeling approaches can be adapted to address problems of interest to cell biologists, relatively few software development efforts have been directed at the field as a whole. The Virtual Cell is a computational environment designed for cell biologists as well as for mathematical biologists and bioengineers. It serves to aid the construction of cell biological models and the generation of simulations from them. The system enables the formulation of both compartmental and spatial models, the latter with either idealized or experimentally derived geometries of one, two or three dimensions.

  3. Computer-aided design of biological circuits using TinkerCell.

    Science.gov (United States)

    Chandran, Deepak; Bergmann, Frank T; Sauro, Herbert M

    2010-01-01

    Synthetic biology is an engineering discipline that builds on modeling practices from systems biology and wet-lab techniques from genetic engineering. As synthetic biology advances, efficient procedures will be developed that will allow a synthetic biologist to design, analyze, and build biological networks. In this idealized pipeline, computer-aided design (CAD) is a necessary component. The role of a CAD application would be to allow efficient transition from a general design to a final product. TinkerCell is a design tool for serving this purpose in synthetic biology. In TinkerCell, users build biological networks using biological parts and modules. The network can be analyzed using one of several functions provided by TinkerCell or custom programs from third-party sources. Since best practices for modeling and constructing synthetic biology networks have not yet been established, TinkerCell is designed as a flexible and extensible application that can adjust itself to changes in the field. © 2010 Landes Bioscience

  4. Integrating interactive computational modeling in biology curricula.

    Directory of Open Access Journals (Sweden)

    Tomáš Helikar

    2015-03-01

    Full Text Available While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

  5. Integrating interactive computational modeling in biology curricula.

    Science.gov (United States)

    Helikar, Tomáš; Cutucache, Christine E; Dahlquist, Lauren M; Herek, Tyler A; Larson, Joshua J; Rogers, Jim A

    2015-03-01

    While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

  6. Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

    OpenAIRE

    Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

    2016-01-01

    In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of tra...

  7. Computational Biology Methods for Characterization of Pluripotent Cells.

    Science.gov (United States)

    Araúzo-Bravo, Marcos J

    2016-01-01

    Pluripotent cells are a powerful tool for regenerative medicine and drug discovery. Several techniques have been developed to induce pluripotency, or to extract pluripotent cells from different tissues and biological fluids. However, the characterization of pluripotency requires tedious, expensive, time-consuming, and not always reliable wet-lab experiments; thus, an easy, standard quality-control protocol of pluripotency assessment remains to be established. Here to help comes the use of high-throughput techniques, and in particular, the employment of gene expression microarrays, which has become a complementary technique for cellular characterization. Research has shown that the transcriptomics comparison with an Embryonic Stem Cell (ESC) of reference is a good approach to assess the pluripotency. Under the premise that the best protocol is a computer software source code, here I propose and explain line by line a software protocol coded in R-Bioconductor for pluripotency assessment based on the comparison of transcriptomics data of pluripotent cells with an ESC of reference. I provide advice for experimental design, warning about possible pitfalls, and guides for results interpretation.

  8. Synthetic biology: engineering molecular computers

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Complicated systems cannot survive the rigors of a chaotic environment, without balancing mechanisms that sense, decide upon and counteract the exerted disturbances. Especially so with living organisms, forced by competition to incredible complexities, escalating also their self-controlling plight. Therefore, they compute. Can we harness biological mechanisms to create artificial computing systems? Biology offers several levels of design abstraction: molecular machines, cells, organisms... ranging from the more easily-defined to the more inherently complex. At the bottom of this stack we find the nucleic acids, RNA and DNA, with their digital structure and relatively precise interactions. They are central enablers of designing artificial biological systems, in the confluence of engineering and biology, that we call Synthetic biology. In the first part, let us follow their trail towards an overview of building computing machines with molecules -- and in the second part, take the case study of iGEM Greece 201...

  9. Spatial Modeling Tools for Cell Biology

    National Research Council Canada - National Science Library

    Przekwas, Andrzej; Friend, Tom; Teixeira, Rodrigo; Chen, Z. J; Wilkerson, Patrick

    2006-01-01

    .... Scientific potentials and military relevance of computational biology and bioinformatics have inspired DARPA/IPTO's visionary BioSPICE project to develop computational framework and modeling tools for cell biology...

  10. Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

    Science.gov (United States)

    Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

    2016-01-01

    In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.

  11. Women are underrepresented in computational biology: An analysis of the scholarly literature in biology, computer science and computational biology.

    Directory of Open Access Journals (Sweden)

    Kevin S Bonham

    2017-10-01

    Full Text Available While women are generally underrepresented in STEM fields, there are noticeable differences between fields. For instance, the gender ratio in biology is more balanced than in computer science. We were interested in how this difference is reflected in the interdisciplinary field of computational/quantitative biology. To this end, we examined the proportion of female authors in publications from the PubMed and arXiv databases. There are fewer female authors on research papers in computational biology, as compared to biology in general. This is true across authorship position, year, and journal impact factor. A comparison with arXiv shows that quantitative biology papers have a higher ratio of female authors than computer science papers, placing computational biology in between its two parent fields in terms of gender representation. Both in biology and in computational biology, a female last author increases the probability of other authors on the paper being female, pointing to a potential role of female PIs in influencing the gender balance.

  12. Women are underrepresented in computational biology: An analysis of the scholarly literature in biology, computer science and computational biology.

    Science.gov (United States)

    Bonham, Kevin S; Stefan, Melanie I

    2017-10-01

    While women are generally underrepresented in STEM fields, there are noticeable differences between fields. For instance, the gender ratio in biology is more balanced than in computer science. We were interested in how this difference is reflected in the interdisciplinary field of computational/quantitative biology. To this end, we examined the proportion of female authors in publications from the PubMed and arXiv databases. There are fewer female authors on research papers in computational biology, as compared to biology in general. This is true across authorship position, year, and journal impact factor. A comparison with arXiv shows that quantitative biology papers have a higher ratio of female authors than computer science papers, placing computational biology in between its two parent fields in terms of gender representation. Both in biology and in computational biology, a female last author increases the probability of other authors on the paper being female, pointing to a potential role of female PIs in influencing the gender balance.

  13. Computational local stiffness analysis of biological cell: High aspect ratio single wall carbon nanotube tip

    Energy Technology Data Exchange (ETDEWEB)

    TermehYousefi, Amin, E-mail: at.tyousefi@gmail.com [Department of Human Intelligence Systems, Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology (Kyutech) (Japan); Bagheri, Samira; Shahnazar, Sheida [Nanotechnology & Catalysis Research Centre (NANOCAT), IPS Building, University Malaya, 50603 Kuala Lumpur (Malaysia); Rahman, Md. Habibur [Department of Computer Science and Engineering, University of Asia Pacific, Green Road, Dhaka-1215 (Bangladesh); Kadri, Nahrizul Adib [Department of Biomedical Engineering, Faculty of Engineering, University Malaya, 50603 Kuala Lumpur (Malaysia)

    2016-02-01

    Carbon nanotubes (CNTs) are potentially ideal tips for atomic force microscopy (AFM) due to the robust mechanical properties, nanoscale diameter and also their ability to be functionalized by chemical and biological components at the tip ends. This contribution develops the idea of using CNTs as an AFM tip in computational analysis of the biological cells. The proposed software was ABAQUS 6.13 CAE/CEL provided by Dassault Systems, which is a powerful finite element (FE) tool to perform the numerical analysis and visualize the interactions between proposed tip and membrane of the cell. Finite element analysis employed for each section and displacement of the nodes located in the contact area was monitored by using an output database (ODB). Mooney–Rivlin hyperelastic model of the cell allows the simulation to obtain a new method for estimating the stiffness and spring constant of the cell. Stress and strain curve indicates the yield stress point which defines as a vertical stress and plan stress. Spring constant of the cell and the local stiffness was measured as well as the applied force of CNT-AFM tip on the contact area of the cell. This reliable integration of CNT-AFM tip process provides a new class of high performance nanoprobes for single biological cell analysis. - Graphical abstract: This contribution develops the idea of using CNTs as an AFM tip in computational analysis of the biological cells. The proposed software was ABAQUS 6.13 CAE/CEL provided by Dassault Systems. Finite element analysis employed for each section and displacement of the nodes located in the contact area was monitored by using an output database (ODB). Mooney–Rivlin hyperelastic model of the cell allows the simulation to obtain a new method for estimating the stiffness and spring constant of the cell. Stress and strain curve indicates the yield stress point which defines as a vertical stress and plan stress. Spring constant of the cell and the local stiffness was measured as well

  14. Biocellion: accelerating computer simulation of multicellular biological system models.

    Science.gov (United States)

    Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

    2014-11-01

    Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  15. Computational protein design-the next generation tool to expand synthetic biology applications.

    Science.gov (United States)

    Gainza-Cirauqui, Pablo; Correia, Bruno Emanuel

    2018-05-02

    One powerful approach to engineer synthetic biology pathways is the assembly of proteins sourced from one or more natural organisms. However, synthetic pathways often require custom functions or biophysical properties not displayed by natural proteins, limitations that could be overcome through modern protein engineering techniques. Structure-based computational protein design is a powerful tool to engineer new functional capabilities in proteins, and it is beginning to have a profound impact in synthetic biology. Here, we review efforts to increase the capabilities of synthetic biology using computational protein design. We focus primarily on computationally designed proteins not only validated in vitro, but also shown to modulate different activities in living cells. Efforts made to validate computational designs in cells can illustrate both the challenges and opportunities in the intersection of protein design and synthetic biology. We also highlight protein design approaches, which although not validated as conveyors of new cellular function in situ, may have rapid and innovative applications in synthetic biology. We foresee that in the near-future, computational protein design will vastly expand the functional capabilities of synthetic cells. Copyright © 2018. Published by Elsevier Ltd.

  16. Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

    International Nuclear Information System (INIS)

    Lewis, Daniel D.; Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng

    2014-01-01

    As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

  17. Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

    Energy Technology Data Exchange (ETDEWEB)

    Lewis, Daniel D. [Integrative Genetics and Genomics, University of California Davis, Davis, CA (United States); Department of Biomedical Engineering, University of California Davis, Davis, CA (United States); Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng, E-mail: cmtan@ucdavis.edu [Department of Biomedical Engineering, University of California Davis, Davis, CA (United States)

    2014-12-09

    As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

  18. TinkerCell: modular CAD tool for synthetic biology

    Science.gov (United States)

    Chandran, Deepak; Bergmann, Frank T; Sauro, Herbert M

    2009-01-01

    Background Synthetic biology brings together concepts and techniques from engineering and biology. In this field, computer-aided design (CAD) is necessary in order to bridge the gap between computational modeling and biological data. Using a CAD application, it would be possible to construct models using available biological "parts" and directly generate the DNA sequence that represents the model, thus increasing the efficiency of design and construction of synthetic networks. Results An application named TinkerCell has been developed in order to serve as a CAD tool for synthetic biology. TinkerCell is a visual modeling tool that supports a hierarchy of biological parts. Each part in this hierarchy consists of a set of attributes that define the part, such as sequence or rate constants. Models that are constructed using these parts can be analyzed using various third-party C and Python programs that are hosted by TinkerCell via an extensive C and Python application programming interface (API). TinkerCell supports the notion of a module, which are networks with interfaces. Such modules can be connected to each other, forming larger modular networks. TinkerCell is a free and open-source project under the Berkeley Software Distribution license. Downloads, documentation, and tutorials are available at . Conclusion An ideal CAD application for engineering biological systems would provide features such as: building and simulating networks, analyzing robustness of networks, and searching databases for components that meet the design criteria. At the current state of synthetic biology, there are no established methods for measuring robustness or identifying components that fit a design. The same is true for databases of biological parts. TinkerCell's flexible modeling framework allows it to cope with changes in the field. Such changes may involve the way parts are characterized or the way synthetic networks are modeled and analyzed computationally. TinkerCell can readily

  19. TinkerCell: modular CAD tool for synthetic biology

    Directory of Open Access Journals (Sweden)

    Bergmann Frank T

    2009-10-01

    Full Text Available Abstract Background Synthetic biology brings together concepts and techniques from engineering and biology. In this field, computer-aided design (CAD is necessary in order to bridge the gap between computational modeling and biological data. Using a CAD application, it would be possible to construct models using available biological "parts" and directly generate the DNA sequence that represents the model, thus increasing the efficiency of design and construction of synthetic networks. Results An application named TinkerCell has been developed in order to serve as a CAD tool for synthetic biology. TinkerCell is a visual modeling tool that supports a hierarchy of biological parts. Each part in this hierarchy consists of a set of attributes that define the part, such as sequence or rate constants. Models that are constructed using these parts can be analyzed using various third-party C and Python programs that are hosted by TinkerCell via an extensive C and Python application programming interface (API. TinkerCell supports the notion of a module, which are networks with interfaces. Such modules can be connected to each other, forming larger modular networks. TinkerCell is a free and open-source project under the Berkeley Software Distribution license. Downloads, documentation, and tutorials are available at http://www.tinkercell.com. Conclusion An ideal CAD application for engineering biological systems would provide features such as: building and simulating networks, analyzing robustness of networks, and searching databases for components that meet the design criteria. At the current state of synthetic biology, there are no established methods for measuring robustness or identifying components that fit a design. The same is true for databases of biological parts. TinkerCell's flexible modeling framework allows it to cope with changes in the field. Such changes may involve the way parts are characterized or the way synthetic networks are modeled

  20. Synthetic analog computation in living cells.

    Science.gov (United States)

    Daniel, Ramiz; Rubens, Jacob R; Sarpeshkar, Rahul; Lu, Timothy K

    2013-05-30

    A central goal of synthetic biology is to achieve multi-signal integration and processing in living cells for diagnostic, therapeutic and biotechnology applications. Digital logic has been used to build small-scale circuits, but other frameworks may be needed for efficient computation in the resource-limited environments of cells. Here we demonstrate that synthetic analog gene circuits can be engineered to execute sophisticated computational functions in living cells using just three transcription factors. Such synthetic analog gene circuits exploit feedback to implement logarithmically linear sensing, addition, ratiometric and power-law computations. The circuits exhibit Weber's law behaviour as in natural biological systems, operate over a wide dynamic range of up to four orders of magnitude and can be designed to have tunable transfer functions. Our circuits can be composed to implement higher-order functions that are well described by both intricate biochemical models and simple mathematical functions. By exploiting analog building-block functions that are already naturally present in cells, this approach efficiently implements arithmetic operations and complex functions in the logarithmic domain. Such circuits may lead to new applications for synthetic biology and biotechnology that require complex computations with limited parts, need wide-dynamic-range biosensing or would benefit from the fine control of gene expression.

  1. Computational Biology and High Performance Computing 2000

    Energy Technology Data Exchange (ETDEWEB)

    Simon, Horst D.; Zorn, Manfred D.; Spengler, Sylvia J.; Shoichet, Brian K.; Stewart, Craig; Dubchak, Inna L.; Arkin, Adam P.

    2000-10-19

    The pace of extraordinary advances in molecular biology has accelerated in the past decade due in large part to discoveries coming from genome projects on human and model organisms. The advances in the genome project so far, happening well ahead of schedule and under budget, have exceeded any dreams by its protagonists, let alone formal expectations. Biologists expect the next phase of the genome project to be even more startling in terms of dramatic breakthroughs in our understanding of human biology, the biology of health and of disease. Only today can biologists begin to envision the necessary experimental, computational and theoretical steps necessary to exploit genome sequence information for its medical impact, its contribution to biotechnology and economic competitiveness, and its ultimate contribution to environmental quality. High performance computing has become one of the critical enabling technologies, which will help to translate this vision of future advances in biology into reality. Biologists are increasingly becoming aware of the potential of high performance computing. The goal of this tutorial is to introduce the exciting new developments in computational biology and genomics to the high performance computing community.

  2. Computational biology

    DEFF Research Database (Denmark)

    Hartmann, Lars Røeboe; Jones, Neil; Simonsen, Jakob Grue

    2011-01-01

    Computation via biological devices has been the subject of close scrutiny since von Neumann’s early work some 60 years ago. In spite of the many relevant works in this field, the notion of programming biological devices seems to be, at best, ill-defined. While many devices are claimed or proved t...

  3. Applicability of Computational Systems Biology in Toxicology

    DEFF Research Database (Denmark)

    Kongsbak, Kristine Grønning; Hadrup, Niels; Audouze, Karine Marie Laure

    2014-01-01

    be used to establish hypotheses on links between the chemical and human diseases. Such information can also be applied for designing more intelligent animal/cell experiments that can test the established hypotheses. Here, we describe how and why to apply an integrative systems biology method......Systems biology as a research field has emerged within the last few decades. Systems biology, often defined as the antithesis of the reductionist approach, integrates information about individual components of a biological system. In integrative systems biology, large data sets from various sources...... and databases are used to model and predict effects of chemicals on, for instance, human health. In toxicology, computational systems biology enables identification of important pathways and molecules from large data sets; tasks that can be extremely laborious when performed by a classical literature search...

  4. Catalyzing Inquiry at the Interface of Computing and Biology

    Energy Technology Data Exchange (ETDEWEB)

    John Wooley; Herbert S. Lin

    2005-10-30

    This study is the first comprehensive NRC study that suggests a high-level intellectual structure for Federal agencies for supporting work at the biology/computing interface. The report seeks to establish the intellectual legitimacy of a fundamentally cross-disciplinary collaboration between biologists and computer scientists. That is, while some universities are increasingly favorable to research at the intersection, life science researchers at other universities are strongly impeded in their efforts to collaborate. This report addresses these impediments and describes proven strategies for overcoming them. An important feature of the report is the use of well-documented examples that describe clearly to individuals not trained in computer science the value and usage of computing across the biological sciences, from genes and proteins to networks and pathways, from organelles to cells, and from individual organisms to populations and ecosystems. It is hoped that these examples will be useful to students in the life sciences to motivate (continued) study in computer science that will enable them to be more facile users of computing in their future biological studies.

  5. Mammalian synthetic biology for studying the cell.

    Science.gov (United States)

    Mathur, Melina; Xiang, Joy S; Smolke, Christina D

    2017-01-02

    Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. © 2017 Mathur et al.

  6. Cell illustrator 4.0: a computational platform for systems biology.

    Science.gov (United States)

    Nagasaki, Masao; Saito, Ayumu; Jeong, Euna; Li, Chen; Kojima, Kaname; Ikeda, Emi; Miyano, Satoru

    2011-01-01

    Cell Illustrator is a software platform for Systems Biology that uses the concept of Petri net for modeling and simulating biopathways. It is intended for biological scientists working at bench. The latest version of Cell Illustrator 4.0 uses Java Web Start technology and is enhanced with new capabilities, including: automatic graph grid layout algorithms using ontology information; tools using Cell System Markup Language (CSML) 3.0 and Cell System Ontology 3.0; parameter search module; high-performance simulation module; CSML database management system; conversion from CSML model to programming languages (FORTRAN, C, C++, Java, Python and Perl); import from SBML, CellML, and BioPAX; and, export to SVG and HTML. Cell Illustrator employs an extension of hybrid Petri net in an object-oriented style so that biopathway models can include objects such as DNA sequence, molecular density, 3D localization information, transcription with frame-shift, translation with codon table, as well as biochemical reactions.

  7. Michael Levitt and Computational Biology

    Science.gov (United States)

    dropdown arrow Site Map A-Z Index Menu Synopsis Michael Levitt and Computational Biology Resources with Michael Levitt, PhD, professor of structural biology at the Stanford University School of Medicine, has function. ... Levitt's early work pioneered computational structural biology, which helped to predict

  8. Applications of membrane computing in systems and synthetic biology

    CERN Document Server

    Gheorghe, Marian; Pérez-Jiménez, Mario

    2014-01-01

    Membrane Computing was introduced as a computational paradigm in Natural Computing. The models introduced, called Membrane (or P) Systems, provide a coherent platform to describe and study living cells as computational systems. Membrane Systems have been investigated for their computational aspects and employed to model problems in other fields, like: Computer Science, Linguistics, Biology, Economy, Computer Graphics, Robotics, etc. Their inherent parallelism, heterogeneity and intrinsic versatility allow them to model a broad range of processes and phenomena, being also an efficient means to solve and analyze problems in a novel way. Membrane Computing has been used to model biological systems, becoming with time a thorough modeling paradigm comparable, in its modeling and predicting capabilities, to more established models in this area. This book is the result of the need to collect, in an organic way, different facets of this paradigm. The chapters of this book, together with the web pages accompanying th...

  9. Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

    Directory of Open Access Journals (Sweden)

    Daniel eLewis

    2014-12-01

    Full Text Available As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo systems, with only a few examples of prominent work done on predicting the dynamics of cell-free systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

  10. UC Merced Center for Computational Biology Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Colvin, Michael; Watanabe, Masakatsu

    2010-11-30

    made possible by the CCB from its inception until August, 2010, at the end of the final extension. Although DOE support for the center ended in August 2010, the CCB will continue to exist and support its original objectives. The research and academic programs fostered by the CCB have led to additional extramural funding from other agencies, and we anticipate that CCB will continue to provide support for quantitative and computational biology program at UC Merced for many years to come. Since its inception in fall 2004, CCB research projects have continuously had a multi-institutional collaboration with Lawrence Livermore National Laboratory (LLNL), and the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, as well as individual collaborators at other sites. CCB affiliated faculty cover a broad range of computational and mathematical research including molecular modeling, cell biology, applied math, evolutional biology, bioinformatics, etc. The CCB sponsored the first distinguished speaker series at UC Merced, which had an important role is spreading the word about the computational biology emphasis at this new campus. One of CCB's original goals is to help train a new generation of biologists who bridge the gap between the computational and life sciences. To archive this goal, by summer 2006, a new program - summer undergraduate internship program, have been established under CCB to train the highly mathematical and computationally intensive Biological Science researchers. By the end of summer 2010, 44 undergraduate students had gone through this program. Out of those participants, 11 students have been admitted to graduate schools and 10 more students are interested in pursuing graduate studies in the sciences. The center is also continuing to facilitate the development and dissemination of undergraduate and graduate course materials based on the latest research in computational biology.

  11. Industrial systems biology and its impact on synthetic biology of yeast cell factories

    DEFF Research Database (Denmark)

    Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

    2016-01-01

    Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools......, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex...... regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal...

  12. Industrial systems biology and its impact on synthetic biology of yeast cell factories.

    Science.gov (United States)

    Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

    2016-06-01

    Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal of developing improved yeast cell factories. Biotechnol. Bioeng. 2016;113: 1164-1170. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  13. A molecular computer to classify cells

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    If only we had a small molecular computer to leverage this disparity, programmable to optimally recognize different classes of cells and, once inside a target cell, to execute an action. Like what a student team researched for this year's synthetic biology iGEM competition.

  14. The case for biological quantum computer elements

    Science.gov (United States)

    Baer, Wolfgang; Pizzi, Rita

    2009-05-01

    An extension to vonNeumann's analysis of quantum theory suggests self-measurement is a fundamental process of Nature. By mapping the quantum computer to the brain architecture we will argue that the cognitive experience results from a measurement of a quantum memory maintained by biological entities. The insight provided by this mapping suggests quantum effects are not restricted to small atomic and nuclear phenomena but are an integral part of our own cognitive experience and further that the architecture of a quantum computer system parallels that of a conscious brain. We will then review the suggestions for biological quantum elements in basic neural structures and address the de-coherence objection by arguing for a self- measurement event model of Nature. We will argue that to first order approximation the universe is composed of isolated self-measurement events which guaranties coherence. Controlled de-coherence is treated as the input/output interactions between quantum elements of a quantum computer and the quantum memory maintained by biological entities cognizant of the quantum calculation results. Lastly we will present stem-cell based neuron experiments conducted by one of us with the aim of demonstrating the occurrence of quantum effects in living neural networks and discuss future research projects intended to reach this objective.

  15. Interactomes to Biological Phase Space: a call to begin thinking at a new level in computational biology.

    Energy Technology Data Exchange (ETDEWEB)

    Davidson, George S.; Brown, William Michael

    2007-09-01

    Techniques for high throughput determinations of interactomes, together with high resolution protein collocalizations maps within organelles and through membranes will soon create a vast resource. With these data, biological descriptions, akin to the high dimensional phase spaces familiar to physicists, will become possible. These descriptions will capture sufficient information to make possible realistic, system-level models of cells. The descriptions and the computational models they enable will require powerful computing techniques. This report is offered as a call to the computational biology community to begin thinking at this scale and as a challenge to develop the required algorithms and codes to make use of the new data.3

  16. Genome Annotation in a Community College Cell Biology Lab

    Science.gov (United States)

    Beagley, C. Timothy

    2013-01-01

    The Biology Department at Salt Lake Community College has used the IMG-ACT toolbox to introduce a genome mapping and annotation exercise into the laboratory portion of its Cell Biology course. This project provides students with an authentic inquiry-based learning experience while introducing them to computational biology and contemporary learning…

  17. A first attempt to bring computational biology into advanced high school biology classrooms.

    Science.gov (United States)

    Gallagher, Suzanne Renick; Coon, William; Donley, Kristin; Scott, Abby; Goldberg, Debra S

    2011-10-01

    Computer science has become ubiquitous in many areas of biological research, yet most high school and even college students are unaware of this. As a result, many college biology majors graduate without adequate computational skills for contemporary fields of biology. The absence of a computational element in secondary school biology classrooms is of growing concern to the computational biology community and biology teachers who would like to acquaint their students with updated approaches in the discipline. We present a first attempt to correct this absence by introducing a computational biology element to teach genetic evolution into advanced biology classes in two local high schools. Our primary goal was to show students how computation is used in biology and why a basic understanding of computation is necessary for research in many fields of biology. This curriculum is intended to be taught by a computational biologist who has worked with a high school advanced biology teacher to adapt the unit for his/her classroom, but a motivated high school teacher comfortable with mathematics and computing may be able to teach this alone. In this paper, we present our curriculum, which takes into consideration the constraints of the required curriculum, and discuss our experiences teaching it. We describe the successes and challenges we encountered while bringing this unit to high school students, discuss how we addressed these challenges, and make suggestions for future versions of this curriculum.We believe that our curriculum can be a valuable seed for further development of computational activities aimed at high school biology students. Further, our experiences may be of value to others teaching computational biology at this level. Our curriculum can be obtained at http://ecsite.cs.colorado.edu/?page_id=149#biology or by contacting the authors.

  18. Computational aspects of systematic biology.

    Science.gov (United States)

    Lilburn, Timothy G; Harrison, Scott H; Cole, James R; Garrity, George M

    2006-06-01

    We review the resources available to systematic biologists who wish to use computers to build classifications. Algorithm development is in an early stage, and only a few examples of integrated applications for systematic biology are available. The availability of data is crucial if systematic biology is to enter the computer age.

  19. Computer support for physiological cell modelling using an ontology on cell physiology.

    Science.gov (United States)

    Takao, Shimayoshi; Kazuhiro, Komurasaki; Akira, Amano; Takeshi, Iwashita; Masanori, Kanazawa; Tetsuya, Matsuda

    2006-01-01

    The development of electrophysiological whole cell models to support the understanding of biological mechanisms is increasing rapidly. Due to the complexity of biological systems, comprehensive cell models, which are composed of many imported sub-models of functional elements, can get quite complicated as well, making computer modification difficult. Here, we propose a computer support to enhance structural changes of cell models, employing the markup languages CellML and our original PMSML (physiological model structure markup language), in addition to a new ontology for cell physiological modelling. In particular, a method to make references from CellML files to the ontology and a method to assist manipulation of model structures using markup languages together with the ontology are reported. Using these methods three software utilities, including a graphical model editor, are implemented. Experimental results proved that these methods are effective for the modification of electrophysiological models.

  20. cellPACK: a virtual mesoscope to model and visualize structural systems biology.

    Science.gov (United States)

    Johnson, Graham T; Autin, Ludovic; Al-Alusi, Mostafa; Goodsell, David S; Sanner, Michel F; Olson, Arthur J

    2015-01-01

    cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10-100 nm) between molecular and cellular biology scales. cellPACK's modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive three-dimensional models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is available as open-source code, with tools for validation of models and with 'recipes' and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org/.

  1. Computing paths and cycles in biological interaction graphs

    Directory of Open Access Journals (Sweden)

    von Kamp Axel

    2009-06-01

    /negative paths and cycles in interaction graphs is an important method for network analysis in Systems Biology. This contribution draws the attention of the community to this important computational problem and provides a number of new algorithms, partially specifically tailored for biological interaction graphs. All algorithms have been implemented in the CellNetAnalyzer framework which can be downloaded for academic use at http://www.mpi-magdeburg.mpg.de/projects/cna/cna.html.

  2. Systems Biology for Organotypic Cell Cultures

    Energy Technology Data Exchange (ETDEWEB)

    Grego, Sonia [RTI International, Research Triangle Park, NC (United States); Dougherty, Edward R. [Texas A & M Univ., College Station, TX (United States); Alexander, Francis J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Auerbach, Scott S. [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Berridge, Brian R. [GlaxoSmithKline, Research Triangle Park, NC (United States); Bittner, Michael L. [Translational Genomics Research Inst., Phoenix, AZ (United States); Casey, Warren [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Cooley, Philip C. [RTI International, Research Triangle Park, NC (United States); Dash, Ajit [HemoShear Therapeutics, Charlottesville, VA (United States); Ferguson, Stephen S. [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Fennell, Timothy R. [RTI International, Research Triangle Park, NC (United States); Hawkins, Brian T. [RTI International, Research Triangle Park, NC (United States); Hickey, Anthony J. [RTI International, Research Triangle Park, NC (United States); Kleensang, Andre [Johns Hopkins Univ., Baltimore, MD (United States). Center for Alternatives to Animal Testing; Liebman, Michael N. [IPQ Analytics, Kennett Square, PA (United States); Martin, Florian [Phillip Morris International, Neuchatel (Switzerland); Maull, Elizabeth A. [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Paragas, Jason [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Qiao, Guilin [Defense Threat Reduction Agency, Ft. Belvoir, VA (United States); Ramaiahgari, Sreenivasa [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Sumner, Susan J. [RTI International, Research Triangle Park, NC (United States); Yoon, Miyoung [The Hamner Inst. for Health Sciences, Research Triangle Park, NC (United States); ScitoVation, Research Triangle Park, NC (United States)

    2016-08-04

    Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomic data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data. This consensus report summarizes the discussions held.

  3. Graphics processing units in bioinformatics, computational biology and systems biology.

    Science.gov (United States)

    Nobile, Marco S; Cazzaniga, Paolo; Tangherloni, Andrea; Besozzi, Daniela

    2017-09-01

    Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools. © The Author 2016. Published by Oxford University Press.

  4. WE-DE-202-00: Connecting Radiation Physics with Computational Biology

    International Nuclear Information System (INIS)

    2016-01-01

    Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological

  5. WE-DE-202-00: Connecting Radiation Physics with Computational Biology

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2016-06-15

    Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological

  6. Structure, function, and behaviour of computational models in systems biology.

    Science.gov (United States)

    Knüpfer, Christian; Beckstein, Clemens; Dittrich, Peter; Le Novère, Nicolas

    2013-05-31

    Systems Biology develops computational models in order to understand biological phenomena. The increasing number and complexity of such "bio-models" necessitate computer support for the overall modelling task. Computer-aided modelling has to be based on a formal semantic description of bio-models. But, even if computational bio-models themselves are represented precisely in terms of mathematical expressions their full meaning is not yet formally specified and only described in natural language. We present a conceptual framework - the meaning facets - which can be used to rigorously specify the semantics of bio-models. A bio-model has a dual interpretation: On the one hand it is a mathematical expression which can be used in computational simulations (intrinsic meaning). On the other hand the model is related to the biological reality (extrinsic meaning). We show that in both cases this interpretation should be performed from three perspectives: the meaning of the model's components (structure), the meaning of the model's intended use (function), and the meaning of the model's dynamics (behaviour). In order to demonstrate the strengths of the meaning facets framework we apply it to two semantically related models of the cell cycle. Thereby, we make use of existing approaches for computer representation of bio-models as much as possible and sketch the missing pieces. The meaning facets framework provides a systematic in-depth approach to the semantics of bio-models. It can serve two important purposes: First, it specifies and structures the information which biologists have to take into account if they build, use and exchange models. Secondly, because it can be formalised, the framework is a solid foundation for any sort of computer support in bio-modelling. The proposed conceptual framework establishes a new methodology for modelling in Systems Biology and constitutes a basis for computer-aided collaborative research.

  7. Modelling, abstraction, and computation in systems biology: A view from computer science.

    Science.gov (United States)

    Melham, Tom

    2013-04-01

    Systems biology is centrally engaged with computational modelling across multiple scales and at many levels of abstraction. Formal modelling, precise and formalised abstraction relationships, and computation also lie at the heart of computer science--and over the past decade a growing number of computer scientists have been bringing their discipline's core intellectual and computational tools to bear on biology in fascinating new ways. This paper explores some of the apparent points of contact between the two fields, in the context of a multi-disciplinary discussion on conceptual foundations of systems biology. Copyright © 2012 Elsevier Ltd. All rights reserved.

  8. Computer Models and Automata Theory in Biology and Medicine

    CERN Document Server

    Baianu, I C

    2004-01-01

    The applications of computers to biological and biomedical problem solving goes back to the very beginnings of computer science, automata theory [1], and mathematical biology [2]. With the advent of more versatile and powerful computers, biological and biomedical applications of computers have proliferated so rapidly that it would be virtually impossible to compile a comprehensive review of all developments in this field. Limitations of computer simulations in biology have also come under close scrutiny, and claims have been made that biological systems have limited information processing power [3]. Such general conjectures do not, however, deter biologists and biomedical researchers from developing new computer applications in biology and medicine. Microprocessors are being widely employed in biological laboratories both for automatic data acquisition/processing and modeling; one particular area, which is of great biomedical interest, involves fast digital image processing and is already established for rout...

  9. Computational Modeling of Biological Systems From Molecules to Pathways

    CERN Document Server

    2012-01-01

    Computational modeling is emerging as a powerful new approach for studying and manipulating biological systems. Many diverse methods have been developed to model, visualize, and rationally alter these systems at various length scales, from atomic resolution to the level of cellular pathways. Processes taking place at larger time and length scales, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. Computational Modeling of Biological Systems: From Molecules to Pathways provides an overview of established computational methods for the modeling of biologically and medically relevant systems. It is suitable for researchers and professionals working in the fields of biophysics, computational biology, systems biology, and molecular medicine.

  10. Final report for Conference Support Grant "From Computational Biophysics to Systems Biology - CBSB12"

    Energy Technology Data Exchange (ETDEWEB)

    Hansmann, Ulrich H.E.

    2012-07-02

    This report summarizes the outcome of the international workshop From Computational Biophysics to Systems Biology (CBSB12) which was held June 3-5, 2012, at the University of Tennessee Conference Center in Knoxville, TN, and supported by DOE through the Conference Support Grant 120174. The purpose of CBSB12 was to provide a forum for the interaction between a data-mining interested systems biology community and a simulation and first-principle oriented computational biophysics/biochemistry community. CBSB12 was the sixth in a series of workshops of the same name organized in recent years, and the second that has been held in the USA. As in previous years, it gave researchers from physics, biology, and computer science an opportunity to acquaint each other with current trends in computational biophysics and systems biology, to explore venues of cooperation, and to establish together a detailed understanding of cells at a molecular level. The conference grant of $10,000 was used to cover registration fees and provide travel fellowships to selected students and postdoctoral scientists. By educating graduate students and providing a forum for young scientists to perform research into the working of cells at a molecular level, the workshop adds to DOE's mission of paving the way to exploit the abilities of living systems to capture, store and utilize energy.

  11. Developmental biology, the stem cell of biological disciplines

    OpenAIRE

    Gilbert, Scott F.

    2017-01-01

    Developmental biology (including embryology) is proposed as "the stem cell of biological disciplines.” Genetics, cell biology, oncology, immunology, evolutionary mechanisms, neurobiology, and systems biology each has its ancestry in developmental biology. Moreover, developmental biology continues to roll on, budding off more disciplines, while retaining its own identity. While its descendant disciplines differentiate into sciences with a restricted set of paradigms, examples, and techniques, ...

  12. Ranked retrieval of Computational Biology models.

    Science.gov (United States)

    Henkel, Ron; Endler, Lukas; Peters, Andre; Le Novère, Nicolas; Waltemath, Dagmar

    2010-08-11

    The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind. Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models. The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models.

  13. Translational environmental biology: cell biology informing conservation.

    Science.gov (United States)

    Traylor-Knowles, Nikki; Palumbi, Stephen R

    2014-05-01

    Typically, findings from cell biology have been beneficial for preventing human disease. However, translational applications from cell biology can also be applied to conservation efforts, such as protecting coral reefs. Recent efforts to understand the cell biological mechanisms maintaining coral health such as innate immunity and acclimatization have prompted new developments in conservation. Similar to biomedicine, we urge that future efforts should focus on better frameworks for biomarker development to protect coral reefs. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. Developmental biology, the stem cell of biological disciplines.

    Science.gov (United States)

    Gilbert, Scott F

    2017-12-01

    Developmental biology (including embryology) is proposed as "the stem cell of biological disciplines." Genetics, cell biology, oncology, immunology, evolutionary mechanisms, neurobiology, and systems biology each has its ancestry in developmental biology. Moreover, developmental biology continues to roll on, budding off more disciplines, while retaining its own identity. While its descendant disciplines differentiate into sciences with a restricted set of paradigms, examples, and techniques, developmental biology remains vigorous, pluripotent, and relatively undifferentiated. In many disciplines, especially in evolutionary biology and oncology, the developmental perspective is being reasserted as an important research program.

  15. Computer simulation in cell radiobiology

    International Nuclear Information System (INIS)

    Yakovlev, A.Y.; Zorin, A.V.

    1988-01-01

    This research monograph demonstrates the possible ways of using stochastic simulation for exploring cell kinetics, emphasizing the effects of cell radiobiology. In vitro kinetics of normal and irradiated cells is the main subject, but some approaches to the simulation of controlled cell systems are considered as well: the epithelium of the small intestine in mice taken as a case in point. Of particular interest is the evaluation of simulation modelling as a tool for gaining insight into biological processes and hence the new inferences from concrete experimental data, concerning regularities in cell population response to irradiation. The book is intended to stimulate interest among computer science specialists in developing new, more efficient means for the simulation of cell systems and to help radiobiologists in interpreting the experimental data

  16. Fostering synergy between cell biology and systems biology.

    Science.gov (United States)

    Eddy, James A; Funk, Cory C; Price, Nathan D

    2015-08-01

    In the shared pursuit of elucidating detailed mechanisms of cell function, systems biology presents a natural complement to ongoing efforts in cell biology. Systems biology aims to characterize biological systems through integrated and quantitative modeling of cellular information. The process of model building and analysis provides value through synthesizing and cataloging information about cells and molecules, predicting mechanisms and identifying generalizable themes, generating hypotheses and guiding experimental design, and highlighting knowledge gaps and refining understanding. In turn, incorporating domain expertise and experimental data is crucial for building towards whole cell models. An iterative cycle of interaction between cell and systems biologists advances the goals of both fields and establishes a framework for mechanistic understanding of the genome-to-phenome relationship. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

  17. Computational biology and bioinformatics in Nigeria.

    Science.gov (United States)

    Fatumo, Segun A; Adoga, Moses P; Ojo, Opeolu O; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi

    2014-04-01

    Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.

  18. Computational biology and bioinformatics in Nigeria.

    Directory of Open Access Journals (Sweden)

    Segun A Fatumo

    2014-04-01

    Full Text Available Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.

  19. Application of computational intelligence to biology

    CERN Document Server

    Sekhar, Akula

    2016-01-01

    This book is a contribution of translational and allied research to the proceedings of the International Conference on Computational Intelligence and Soft Computing. It explains how various computational intelligence techniques can be applied to investigate various biological problems. It is a good read for Research Scholars, Engineers, Medical Doctors and Bioinformatics researchers.

  20. The fusion of biology, computer science, and engineering: towards efficient and successful synthetic biology.

    Science.gov (United States)

    Linshiz, Gregory; Goldberg, Alex; Konry, Tania; Hillson, Nathan J

    2012-01-01

    Synthetic biology is a nascent field that emerged in earnest only around the turn of the millennium. It aims to engineer new biological systems and impart new biological functionality, often through genetic modifications. The design and construction of new biological systems is a complex, multistep process, requiring multidisciplinary collaborative efforts from "fusion" scientists who have formal training in computer science or engineering, as well as hands-on biological expertise. The public has high expectations for synthetic biology and eagerly anticipates the development of solutions to the major challenges facing humanity. This article discusses laboratory practices and the conduct of research in synthetic biology. It argues that the fusion science approach, which integrates biology with computer science and engineering best practices, including standardization, process optimization, computer-aided design and laboratory automation, miniaturization, and systematic management, will increase the predictability and reproducibility of experiments and lead to breakthroughs in the construction of new biological systems. The article also discusses several successful fusion projects, including the development of software tools for DNA construction design automation, recursive DNA construction, and the development of integrated microfluidics systems.

  1. Bioinformatics approaches to single-cell analysis in developmental biology.

    Science.gov (United States)

    Yalcin, Dicle; Hakguder, Zeynep M; Otu, Hasan H

    2016-03-01

    Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging and omics techniques on single cells. There have been improvements in computational single-cell image analysis in developmental biology regarding feature extraction, segmentation, image enhancement and machine learning, handling limitations of optical resolution to gain new perspectives from the raw microscopy images. Omics approaches, such as transcriptomics, genomics and epigenomics, targeting gene and small RNA expression, single nucleotide and structural variations and methylation and histone modifications, rely heavily on high-throughput sequencing technologies. Although there are well-established bioinformatics methods for analysis of sequence data, there are limited bioinformatics approaches which address experimental design, sample size considerations, amplification bias, normalization, differential expression, coverage, clustering and classification issues, specifically applied at the single-cell level. In this review, we summarize biological and technological advancements, discuss challenges faced in the aforementioned data acquisition and analysis issues and present future prospects for application of single-cell analyses to developmental biology. © The Author 2015. Published by Oxford University Press on behalf of the European

  2. Computational biology for ageing

    Science.gov (United States)

    Wieser, Daniela; Papatheodorou, Irene; Ziehm, Matthias; Thornton, Janet M.

    2011-01-01

    High-throughput genomic and proteomic technologies have generated a wealth of publicly available data on ageing. Easy access to these data, and their computational analysis, is of great importance in order to pinpoint the causes and effects of ageing. Here, we provide a description of the existing databases and computational tools on ageing that are available for researchers. We also describe the computational approaches to data interpretation in the field of ageing including gene expression, comparative and pathway analyses, and highlight the challenges for future developments. We review recent biological insights gained from applying bioinformatics methods to analyse and interpret ageing data in different organisms, tissues and conditions. PMID:21115530

  3. Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges.

    Science.gov (United States)

    Yin, Zekun; Lan, Haidong; Tan, Guangming; Lu, Mian; Vasilakos, Athanasios V; Liu, Weiguo

    2017-01-01

    The last decade has witnessed an explosion in the amount of available biological sequence data, due to the rapid progress of high-throughput sequencing projects. However, the biological data amount is becoming so great that traditional data analysis platforms and methods can no longer meet the need to rapidly perform data analysis tasks in life sciences. As a result, both biologists and computer scientists are facing the challenge of gaining a profound insight into the deepest biological functions from big biological data. This in turn requires massive computational resources. Therefore, high performance computing (HPC) platforms are highly needed as well as efficient and scalable algorithms that can take advantage of these platforms. In this paper, we survey the state-of-the-art HPC platforms for big biological data analytics. We first list the characteristics of big biological data and popular computing platforms. Then we provide a taxonomy of different biological data analysis applications and a survey of the way they have been mapped onto various computing platforms. After that, we present a case study to compare the efficiency of different computing platforms for handling the classical biological sequence alignment problem. At last we discuss the open issues in big biological data analytics.

  4. Genome annotation in a community college cell biology lab.

    Science.gov (United States)

    Beagley, C Timothy

    2013-01-01

    The Biology Department at Salt Lake Community College has used the IMG-ACT toolbox to introduce a genome mapping and annotation exercise into the laboratory portion of its Cell Biology course. This project provides students with an authentic inquiry-based learning experience while introducing them to computational biology and contemporary learning skills. Additionally, the project strengthens student understanding of the scientific method and contributes to student learning gains in curricular objectives centered around basic molecular biology, specifically, the Central Dogma. Importantly, inclusion of this project in the laboratory course provides students with a positive learning environment and allows for the use of cooperative learning strategies to increase overall student success. Copyright © 2012 International Union of Biochemistry and Molecular Biology, Inc.

  5. Computational structural biology: methods and applications

    National Research Council Canada - National Science Library

    Schwede, Torsten; Peitsch, Manuel Claude

    2008-01-01

    ... sequencing reinforced the observation that structural information is needed to understand the detailed function and mechanism of biological molecules such as enzyme reactions and molecular recognition events. Furthermore, structures are obviously key to the design of molecules with new or improved functions. In this context, computational structural biology...

  6. Discovery of novel bacterial toxins by genomics and computational biology.

    Science.gov (United States)

    Doxey, Andrew C; Mansfield, Michael J; Montecucco, Cesare

    2018-06-01

    Hundreds and hundreds of bacterial protein toxins are presently known. Traditionally, toxin identification begins with pathological studies of bacterial infectious disease. Following identification and cultivation of a bacterial pathogen, the protein toxin is purified from the culture medium and its pathogenic activity is studied using the methods of biochemistry and structural biology, cell biology, tissue and organ biology, and appropriate animal models, supplemented by bioimaging techniques. The ongoing and explosive development of high-throughput DNA sequencing and bioinformatic approaches have set in motion a revolution in many fields of biology, including microbiology. One consequence is that genes encoding novel bacterial toxins can be identified by bioinformatic and computational methods based on previous knowledge accumulated from studies of the biology and pathology of thousands of known bacterial protein toxins. Starting from the paradigmatic cases of diphtheria toxin, tetanus and botulinum neurotoxins, this review discusses traditional experimental approaches as well as bioinformatics and genomics-driven approaches that facilitate the discovery of novel bacterial toxins. We discuss recent work on the identification of novel botulinum-like toxins from genera such as Weissella, Chryseobacterium, and Enteroccocus, and the implications of these computationally identified toxins in the field. Finally, we discuss the promise of metagenomics in the discovery of novel toxins and their ecological niches, and present data suggesting the existence of uncharacterized, botulinum-like toxin genes in insect gut metagenomes. Copyright © 2018. Published by Elsevier Ltd.

  7. Toward computational cumulative biology by combining models of biological datasets.

    Science.gov (United States)

    Faisal, Ali; Peltonen, Jaakko; Georgii, Elisabeth; Rung, Johan; Kaski, Samuel

    2014-01-01

    A main challenge of data-driven sciences is how to make maximal use of the progressively expanding databases of experimental datasets in order to keep research cumulative. We introduce the idea of a modeling-based dataset retrieval engine designed for relating a researcher's experimental dataset to earlier work in the field. The search is (i) data-driven to enable new findings, going beyond the state of the art of keyword searches in annotations, (ii) modeling-driven, to include both biological knowledge and insights learned from data, and (iii) scalable, as it is accomplished without building one unified grand model of all data. Assuming each dataset has been modeled beforehand, by the researchers or automatically by database managers, we apply a rapidly computable and optimizable combination model to decompose a new dataset into contributions from earlier relevant models. By using the data-driven decomposition, we identify a network of interrelated datasets from a large annotated human gene expression atlas. While tissue type and disease were major driving forces for determining relevant datasets, the found relationships were richer, and the model-based search was more accurate than the keyword search; moreover, it recovered biologically meaningful relationships that are not straightforwardly visible from annotations-for instance, between cells in different developmental stages such as thymocytes and T-cells. Data-driven links and citations matched to a large extent; the data-driven links even uncovered corrections to the publication data, as two of the most linked datasets were not highly cited and turned out to have wrong publication entries in the database.

  8. Molecular biology of the cell

    CERN Document Server

    Alberts, Bruce; Lewis, Julian

    2000-01-01

    Molecular Biology of the Cell is the classic in-dept text reference in cell biology. By extracting the fundamental concepts from this enormous and ever-growing field, the authors tell the story of cell biology, and create a coherent framework through which non-expert readers may approach the subject. Written in clear and concise language, and beautifully illustrated, the book is enjoyable to read, and it provides a clear sense of the excitement of modern biology. Molecular Biology of the Cell sets forth the current understanding of cell biology (completely updated as of Autumn 2001), and it explores the intriguing implications and possibilities of the great deal that remains unknown. The hallmark features of previous editions continue in the Fourth Edition. The book is designed with a clean and open, single-column layout. The art program maintains a completely consistent format and style, and includes over 1,600 photographs, electron micrographs, and original drawings by the authors. Clear and concise concept...

  9. Biological fuel cells and their applications

    OpenAIRE

    Shukla, AK; Suresh, P; Berchmans, S; Rajendran, A

    2004-01-01

    One type of genuine fuel cell that does hold promise in the long-term is the biological fuel cell. Unlike conventional fuel cells, which employ hydrogen, ethanol and methanol as fuel, biological fuel cells use organic products produced by metabolic processes or use organic electron donors utilized in the growth processes as fuels for current generation. A distinctive feature of biological fuel cells is that the electrode reactions are controlled by biocatalysts, i.e. the biological redox-reac...

  10. Multiscale models and stochastic simulation methods for computing rare but key binding events in cell biology

    Energy Technology Data Exchange (ETDEWEB)

    Guerrier, C. [Applied Mathematics and Computational Biology, IBENS, Ecole Normale Supérieure, 46 rue d' Ulm, 75005 Paris (France); Holcman, D., E-mail: david.holcman@ens.fr [Applied Mathematics and Computational Biology, IBENS, Ecole Normale Supérieure, 46 rue d' Ulm, 75005 Paris (France); Mathematical Institute, Oxford OX2 6GG, Newton Institute (United Kingdom)

    2017-07-01

    The main difficulty in simulating diffusion processes at a molecular level in cell microdomains is due to the multiple scales involving nano- to micrometers. Few to many particles have to be simulated and simultaneously tracked while there are exploring a large portion of the space for binding small targets, such as buffers or active sites. Bridging the small and large spatial scales is achieved by rare events representing Brownian particles finding small targets and characterized by long-time distribution. These rare events are the bottleneck of numerical simulations. A naive stochastic simulation requires running many Brownian particles together, which is computationally greedy and inefficient. Solving the associated partial differential equations is also difficult due to the time dependent boundary conditions, narrow passages and mixed boundary conditions at small windows. We present here two reduced modeling approaches for a fast computation of diffusing fluxes in microdomains. The first approach is based on a Markov mass-action law equations coupled to a Markov chain. The second is a Gillespie's method based on the narrow escape theory for coarse-graining the geometry of the domain into Poissonian rates. The main application concerns diffusion in cellular biology, where we compute as an example the distribution of arrival times of calcium ions to small hidden targets to trigger vesicular release.

  11. Multiscale models and stochastic simulation methods for computing rare but key binding events in cell biology

    International Nuclear Information System (INIS)

    Guerrier, C.; Holcman, D.

    2017-01-01

    The main difficulty in simulating diffusion processes at a molecular level in cell microdomains is due to the multiple scales involving nano- to micrometers. Few to many particles have to be simulated and simultaneously tracked while there are exploring a large portion of the space for binding small targets, such as buffers or active sites. Bridging the small and large spatial scales is achieved by rare events representing Brownian particles finding small targets and characterized by long-time distribution. These rare events are the bottleneck of numerical simulations. A naive stochastic simulation requires running many Brownian particles together, which is computationally greedy and inefficient. Solving the associated partial differential equations is also difficult due to the time dependent boundary conditions, narrow passages and mixed boundary conditions at small windows. We present here two reduced modeling approaches for a fast computation of diffusing fluxes in microdomains. The first approach is based on a Markov mass-action law equations coupled to a Markov chain. The second is a Gillespie's method based on the narrow escape theory for coarse-graining the geometry of the domain into Poissonian rates. The main application concerns diffusion in cellular biology, where we compute as an example the distribution of arrival times of calcium ions to small hidden targets to trigger vesicular release.

  12. Stochastic processes, multiscale modeling, and numerical methods for computational cellular biology

    CERN Document Server

    2017-01-01

    This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of s...

  13. Micro-Computers in Biology Inquiry.

    Science.gov (United States)

    Barnato, Carolyn; Barrett, Kathy

    1981-01-01

    Describes the modification of computer programs (BISON and POLLUT) to accommodate species and areas indigenous to the Pacific Coast area. Suggests that these programs, suitable for PET microcomputers, may foster a long-term, ongoing, inquiry-directed approach in biology. (DS)

  14. Multiway modeling and analysis in stem cell systems biology

    Directory of Open Access Journals (Sweden)

    Vandenberg Scott L

    2008-07-01

    Full Text Available Abstract Background Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.. A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. Results We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a

  15. 6th International Conference on Practical Applications of Computational Biology & Bioinformatics

    CERN Document Server

    Luscombe, Nicholas; Fdez-Riverola, Florentino; Rodríguez, Juan; Practical Applications of Computational Biology & Bioinformatics

    2012-01-01

    The growth in the Bioinformatics and Computational Biology fields over the last few years has been remarkable.. The analysis of the datasets of Next Generation Sequencing needs new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Also Systems Biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. This book presents the results of the  6th International Conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, 28-30th March, 2012 which brought together interdisciplinary scientists that have a strong background in the biological and computational sciences.

  16. Systems Biology and Stem Cell Pluripotency

    DEFF Research Database (Denmark)

    Mashayekhi, Kaveh; Hall, Vanessa Jane; Freude, Kristine

    2016-01-01

    Recent breakthroughs in stem cell biology have accelerated research in the area of regenerative medicine. Over the past years, it has become possible to derive patient-specific stem cells which can be used to generate different cell populations for potential cell therapy. Systems biological...... modeling of stem cell pluripotency and differentiation have largely been based on prior knowledge of signaling pathways, gene regulatory networks, and epigenetic factors. However, there is a great need to extend the complexity of the modeling and to integrate different types of data, which would further...... improve systems biology and its uses in the field. In this chapter, we first give a general background on stem cell biology and regenerative medicine. Stem cell potency is introduced together with the hierarchy of stem cells ranging from pluripotent embryonic stem cells (ESCs) and induced pluripotent stem...

  17. Studying cell biology in the skin.

    Science.gov (United States)

    Morrow, Angel; Lechler, Terry

    2015-11-15

    Advances in cell biology have often been driven by studies in diverse organisms and cell types. Although there are technical reasons for why different cell types are used, there are also important physiological reasons. For example, ultrastructural studies of vesicle transport were aided by the use of professional secretory cell types. The use of tissues/primary cells has the advantage not only of using cells that are adapted to the use of certain cell biological machinery, but also of highlighting the physiological roles of this machinery. Here we discuss advantages of the skin as a model system. We discuss both advances in cell biology that used the skin as a driving force and future prospects for use of the skin to understand basic cell biology. A unique combination of characteristics and tools makes the skin a useful in vivo model system for many cell biologists. © 2015 Morrow and Lechler. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  18. How Computers are Arming biology!

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 23; Issue 1. In-vitro to In-silico - How Computers are Arming biology! Geetha Sugumaran Sushila Rajagopal. Face to Face Volume 23 Issue 1 January 2018 pp 83-102. Fulltext. Click here to view fulltext PDF. Permanent link:

  19. Computational Biology Support: RECOMB Conference Series (Conference Support)

    Energy Technology Data Exchange (ETDEWEB)

    Michael Waterman

    2006-06-15

    This funding was support for student and postdoctoral attendance at the Annual Recomb Conference from 2001 to 2005. The RECOMB Conference series was founded in 1997 to provide a scientific forum for theoretical advances in computational biology and their applications in molecular biology and medicine. The conference series aims at attracting research contributions in all areas of computational molecular biology. Typical, but not exclusive, the topics of interest are: Genomics, Molecular sequence analysis, Recognition of genes and regulatory elements, Molecular evolution, Protein structure, Structural genomics, Gene Expression, Gene Networks, Drug Design, Combinatorial libraries, Computational proteomics, and Structural and functional genomics. The origins of the conference came from the mathematical and computational side of the field, and there remains to be a certain focus on computational advances. However, the effective use of computational techniques to biological innovation is also an important aspect of the conference. The conference had a growing number of attendees, topping 300 in recent years and often exceeding 500. The conference program includes between 30 and 40 contributed papers, that are selected by a international program committee with around 30 experts during a rigorous review process rivaling the editorial procedure for top-rate scientific journals. In previous years papers selection has been made from up to 130--200 submissions from well over a dozen countries. 10-page extended abstracts of the contributed papers are collected in a volume published by ACM Press and Springer, and are available at the conference. Full versions of a selection of the papers are published annually in a special issue of the Journal of Computational Biology devoted to the RECOMB Conference. A further point in the program is a lively poster session. From 120-300 posters have been presented each year at RECOMB 2000. One of the highlights of each RECOMB conference is a

  20. Mammalian cell biology

    International Nuclear Information System (INIS)

    Elkind, M.M.

    1979-01-01

    This section contains summaries of research on mechanisms of lethality and radioinduced changes in mammalian cell properties, new cell systems for the study of the biology of mutation and neoplastic transformation, and comparative properties of ionizing radiations

  1. Evolutionary cell biology: two origins, one objective.

    Science.gov (United States)

    Lynch, Michael; Field, Mark C; Goodson, Holly V; Malik, Harmit S; Pereira-Leal, José B; Roos, David S; Turkewitz, Aaron P; Sazer, Shelley

    2014-12-02

    All aspects of biological diversification ultimately trace to evolutionary modifications at the cellular level. This central role of cells frames the basic questions as to how cells work and how cells come to be the way they are. Although these two lines of inquiry lie respectively within the traditional provenance of cell biology and evolutionary biology, a comprehensive synthesis of evolutionary and cell-biological thinking is lacking. We define evolutionary cell biology as the fusion of these two eponymous fields with the theoretical and quantitative branches of biochemistry, biophysics, and population genetics. The key goals are to develop a mechanistic understanding of general evolutionary processes, while specifically infusing cell biology with an evolutionary perspective. The full development of this interdisciplinary field has the potential to solve numerous problems in diverse areas of biology, including the degree to which selection, effectively neutral processes, historical contingencies, and/or constraints at the chemical and biophysical levels dictate patterns of variation for intracellular features. These problems can now be examined at both the within- and among-species levels, with single-cell methodologies even allowing quantification of variation within genotypes. Some results from this emerging field have already had a substantial impact on cell biology, and future findings will significantly influence applications in agriculture, medicine, environmental science, and synthetic biology.

  2. The thermodynamic efficiency of computations made in cells across the range of life

    Science.gov (United States)

    Kempes, Christopher P.; Wolpert, David; Cohen, Zachary; Pérez-Mercader, Juan

    2017-11-01

    Biological organisms must perform computation as they grow, reproduce and evolve. Moreover, ever since Landauer's bound was proposed, it has been known that all computation has some thermodynamic cost-and that the same computation can be achieved with greater or smaller thermodynamic cost depending on how it is implemented. Accordingly an important issue concerning the evolution of life is assessing the thermodynamic efficiency of the computations performed by organisms. This issue is interesting both from the perspective of how close life has come to maximally efficient computation (presumably under the pressure of natural selection), and from the practical perspective of what efficiencies we might hope that engineered biological computers might achieve, especially in comparison with current computational systems. Here we show that the computational efficiency of translation, defined as free energy expended per amino acid operation, outperforms the best supercomputers by several orders of magnitude, and is only about an order of magnitude worse than the Landauer bound. However, this efficiency depends strongly on the size and architecture of the cell in question. In particular, we show that the useful efficiency of an amino acid operation, defined as the bulk energy per amino acid polymerization, decreases for increasing bacterial size and converges to the polymerization cost of the ribosome. This cost of the largest bacteria does not change in cells as we progress through the major evolutionary shifts to both single- and multicellular eukaryotes. However, the rates of total computation per unit mass are non-monotonic in bacteria with increasing cell size, and also change across different biological architectures, including the shift from unicellular to multicellular eukaryotes. This article is part of the themed issue 'Reconceptualizing the origins of life'.

  3. 9th International Conference on Practical Applications of Computational Biology and Bioinformatics

    CERN Document Server

    Rocha, Miguel; Fdez-Riverola, Florentino; Paz, Juan

    2015-01-01

    This proceedings presents recent practical applications of Computational Biology and  Bioinformatics. It contains the proceedings of the 9th International Conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, at June 3rd-5th, 2015. The International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB) is an annual international meeting dedicated to emerging and challenging applied research in Bioinformatics and Computational Biology. Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis o...

  4. Extending and Applying Spartan to Perform Temporal Sensitivity Analyses for Predicting Changes in Influential Biological Pathways in Computational Models.

    Science.gov (United States)

    Alden, Kieran; Timmis, Jon; Andrews, Paul S; Veiga-Fernandes, Henrique; Coles, Mark

    2017-01-01

    Through integrating real time imaging, computational modelling, and statistical analysis approaches, previous work has suggested that the induction of and response to cell adhesion factors is the key initiating pathway in early lymphoid tissue development, in contrast to the previously accepted view that the process is triggered by chemokine mediated cell recruitment. These model derived hypotheses were developed using spartan, an open-source sensitivity analysis toolkit designed to establish and understand the relationship between a computational model and the biological system that model captures. Here, we extend the functionality available in spartan to permit the production of statistical analyses that contrast the behavior exhibited by a computational model at various simulated time-points, enabling a temporal analysis that could suggest whether the influence of biological mechanisms changes over time. We exemplify this extended functionality by using the computational model of lymphoid tissue development as a time-lapse tool. By generating results at twelve- hour intervals, we show how the extensions to spartan have been used to suggest that lymphoid tissue development could be biphasic, and predict the time-point when a switch in the influence of biological mechanisms might occur.

  5. Computational biology in the cloud: methods and new insights from computing at scale.

    Science.gov (United States)

    Kasson, Peter M

    2013-01-01

    The past few years have seen both explosions in the size of biological data sets and the proliferation of new, highly flexible on-demand computing capabilities. The sheer amount of information available from genomic and metagenomic sequencing, high-throughput proteomics, experimental and simulation datasets on molecular structure and dynamics affords an opportunity for greatly expanded insight, but it creates new challenges of scale for computation, storage, and interpretation of petascale data. Cloud computing resources have the potential to help solve these problems by offering a utility model of computing and storage: near-unlimited capacity, the ability to burst usage, and cheap and flexible payment models. Effective use of cloud computing on large biological datasets requires dealing with non-trivial problems of scale and robustness, since performance-limiting factors can change substantially when a dataset grows by a factor of 10,000 or more. New computing paradigms are thus often needed. The use of cloud platforms also creates new opportunities to share data, reduce duplication, and to provide easy reproducibility by making the datasets and computational methods easily available.

  6. Feedback dynamics and cell function: Why systems biology is called Systems Biology.

    Science.gov (United States)

    Wolkenhauer, Olaf; Mesarovic, Mihajlo

    2005-05-01

    A new paradigm, like Systems Biology, should challenge the way research has been conducted previously. This Opinion article aims to present Systems Biology, not as the application of engineering principles to biology but as a merger of systems- and control theory with molecular- and cell biology. In our view, the central dogma of Systems Biology is that it is system dynamics that gives rise to the functioning and function of cells. The concepts of feedback regulation and control of pathways and the coordination of cell function are emphasized as an important area of Systems Biology research. The hurdles and risks for this area are discussed from the perspective of dynamic pathway modelling. Most of all, the aim of this article is to promote mathematical modelling and simulation as a part of molecular- and cell biology. Systems Biology is a success if it is widely accepted that there is nothing more practical than a good theory.

  7. Computational Biomechanics Theoretical Background and BiologicalBiomedical Problems

    CERN Document Server

    Tanaka, Masao; Nakamura, Masanori

    2012-01-01

    Rapid developments have taken place in biological/biomedical measurement and imaging technologies as well as in computer analysis and information technologies. The increase in data obtained with such technologies invites the reader into a virtual world that represents realistic biological tissue or organ structures in digital form and allows for simulation and what is called “in silico medicine.” This volume is the third in a textbook series and covers both the basics of continuum mechanics of biosolids and biofluids and the theoretical core of computational methods for continuum mechanics analyses. Several biomechanics problems are provided for better understanding of computational modeling and analysis. Topics include the mechanics of solid and fluid bodies, fundamental characteristics of biosolids and biofluids, computational methods in biomechanics analysis/simulation, practical problems in orthopedic biomechanics, dental biomechanics, ophthalmic biomechanics, cardiovascular biomechanics, hemodynamics...

  8. DOE EPSCoR Initiative in Structural and computational Biology/Bioinformatics

    Energy Technology Data Exchange (ETDEWEB)

    Wallace, Susan S.

    2008-02-21

    The overall goal of the DOE EPSCoR Initiative in Structural and Computational Biology was to enhance the competiveness of Vermont research in these scientific areas. To develop self-sustaining infrastructure, we increased the critical mass of faculty, developed shared resources that made junior researchers more competitive for federal research grants, implemented programs to train graduate and undergraduate students who participated in these research areas and provided seed money for research projects. During the time period funded by this DOE initiative: (1) four new faculty were recruited to the University of Vermont using DOE resources, three in Computational Biology and one in Structural Biology; (2) technical support was provided for the Computational and Structural Biology facilities; (3) twenty-two graduate students were directly funded by fellowships; (4) fifteen undergraduate students were supported during the summer; and (5) twenty-eight pilot projects were supported. Taken together these dollars resulted in a plethora of published papers, many in high profile journals in the fields and directly impacted competitive extramural funding based on structural or computational biology resulting in 49 million dollars awarded in grants (Appendix I), a 600% return on investment by DOE, the State and University.

  9. 7th International Conference on Practical Applications of Computational Biology & Bioinformatics

    CERN Document Server

    Nanni, Loris; Rocha, Miguel; Fdez-Riverola, Florentino

    2013-01-01

    The growth in the Bioinformatics and Computational Biology fields over the last few years has been remarkable and the trend is to increase its pace. In fact, the need for computational techniques that can efficiently handle the huge amounts of data produced by the new experimental techniques in Biology is still increasing driven by new advances in Next Generation Sequencing, several types of the so called omics data and image acquisition, just to name a few. The analysis of the datasets that produces and its integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Within this scenario of increasing data availability, Systems Biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. Indeed, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we ...

  10. Computational systems biology and dose-response modeling in relation to new directions in toxicity testing.

    Science.gov (United States)

    Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E; Conolly, Rory B

    2010-02-01

    The new paradigm envisioned for toxicity testing in the 21st century advocates shifting from the current animal-based testing process to a combination of in vitro cell-based studies, high-throughput techniques, and in silico modeling. A strategic component of the vision is the adoption of the systems biology approach to acquire, analyze, and interpret toxicity pathway data. As key toxicity pathways are identified and their wiring details elucidated using traditional and high-throughput techniques, there is a pressing need to understand their qualitative and quantitative behaviors in response to perturbation by both physiological signals and exogenous stressors. The complexity of these molecular networks makes the task of understanding cellular responses merely by human intuition challenging, if not impossible. This process can be aided by mathematical modeling and computer simulation of the networks and their dynamic behaviors. A number of theoretical frameworks were developed in the last century for understanding dynamical systems in science and engineering disciplines. These frameworks, which include metabolic control analysis, biochemical systems theory, nonlinear dynamics, and control theory, can greatly facilitate the process of organizing, analyzing, and understanding toxicity pathways. Such analysis will require a comprehensive examination of the dynamic properties of "network motifs"--the basic building blocks of molecular circuits. Network motifs like feedback and feedforward loops appear repeatedly in various molecular circuits across cell types and enable vital cellular functions like homeostasis, all-or-none response, memory, and biological rhythm. These functional motifs and associated qualitative and quantitative properties are the predominant source of nonlinearities observed in cellular dose response data. Complex response behaviors can arise from toxicity pathways built upon combinations of network motifs. While the field of computational cell

  11. Learning Cell Biology as a Team: A Project-Based Approach to Upper-Division Cell Biology

    Science.gov (United States)

    Wright, Robin; Boggs, James

    2002-01-01

    To help students develop successful strategies for learning how to learn and communicate complex information in cell biology, we developed a quarter-long cell biology class based on team projects. Each team researches a particular human disease and presents information about the cellular structure or process affected by the disease, the cellular…

  12. Teaching Cell Biology in Primary Schools

    Directory of Open Access Journals (Sweden)

    Francele de Abreu Carlan

    2014-01-01

    Full Text Available Basic concepts of cell biology are essential for scientific literacy. However, because many aspects of cell theory and cell functioning are quite abstract, students experience difficulties understanding them. In this study, we investigated whether diverse teaching resources such as the use of replicas of Leeuwenhoek’s microscope, visualization of cells using an optical microscope, construction of three-dimensional cell models, and reading of a comic book about cells could mitigate the difficulties encountered when teaching cell biology to 8th-grade primary school students. The results suggest that these didactic activities improve students’ ability to learn concrete concepts about cell biology, such as the composition of living beings, growth, and cicatrization. Also, the development of skills was observed, as, for example, the notion of cell size. However, no significant improvements were observed in students’ ability to learn about abstract topics, such as the structures of subcellular organelles and their functions. These results suggest that many students in this age have not yet concluded Piaget’s concrete operational stage, indicating that the concepts required for the significant learning of abstract subjects need to be explored more thoroughly in the process of designing programs that introduce primary school students to cell biology.

  13. Defining Biological Networks for Noise Buffering and Signaling Sensitivity Using Approximate Bayesian Computation

    Directory of Open Access Journals (Sweden)

    Shuqiang Wang

    2014-01-01

    Full Text Available Reliable information processing in cells requires high sensitivity to changes in the input signal but low sensitivity to random fluctuations in the transmitted signal. There are often many alternative biological circuits qualifying for this biological function. Distinguishing theses biological models and finding the most suitable one are essential, as such model ranking, by experimental evidence, will help to judge the support of the working hypotheses forming each model. Here, we employ the approximate Bayesian computation (ABC method based on sequential Monte Carlo (SMC to search for biological circuits that can maintain signaling sensitivity while minimizing noise propagation, focusing on cases where the noise is characterized by rapid fluctuations. By systematically analyzing three-component circuits, we rank these biological circuits and identify three-basic-biological-motif buffering noise while maintaining sensitivity to long-term changes in input signals. We discuss in detail a particular implementation in control of nutrient homeostasis in yeast. The principal component analysis of the posterior provides insight into the nature of the reaction between nodes.

  14. A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

    Science.gov (United States)

    Pârvu, Ovidiu; Gilbert, David

    2016-01-01

    , the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems.

  15. Biological 2-Input Decoder Circuit in Human Cells

    Science.gov (United States)

    2015-01-01

    Decoders are combinational circuits that convert information from n inputs to a maximum of 2n outputs. This operation is of major importance in computing systems yet it is vastly underexplored in synthetic biology. Here, we present a synthetic gene network architecture that operates as a biological decoder in human cells, converting 2 inputs to 4 outputs. As a proof-of-principle, we use small molecules to emulate the two inputs and fluorescent reporters as the corresponding four outputs. The experiments are performed using transient transfections in human kidney embryonic cells and the characterization by fluorescence microscopy and flow cytometry. We show a clear separation between the ON and OFF mean fluorescent intensity states. Additionally, we adopt the integrated mean fluorescence intensity for the characterization of the circuit and show that this metric is more robust to transfection conditions when compared to the mean fluorescent intensity. To conclude, we present the first implementation of a genetic decoder. This combinational system can be valuable toward engineering higher-order circuits as well as accommodate a multiplexed interface with endogenous cellular functions. PMID:24694115

  16. Biological 2-input decoder circuit in human cells.

    Science.gov (United States)

    Guinn, Michael; Bleris, Leonidas

    2014-08-15

    Decoders are combinational circuits that convert information from n inputs to a maximum of 2(n) outputs. This operation is of major importance in computing systems yet it is vastly underexplored in synthetic biology. Here, we present a synthetic gene network architecture that operates as a biological decoder in human cells, converting 2 inputs to 4 outputs. As a proof-of-principle, we use small molecules to emulate the two inputs and fluorescent reporters as the corresponding four outputs. The experiments are performed using transient transfections in human kidney embryonic cells and the characterization by fluorescence microscopy and flow cytometry. We show a clear separation between the ON and OFF mean fluorescent intensity states. Additionally, we adopt the integrated mean fluorescence intensity for the characterization of the circuit and show that this metric is more robust to transfection conditions when compared to the mean fluorescent intensity. To conclude, we present the first implementation of a genetic decoder. This combinational system can be valuable toward engineering higher-order circuits as well as accommodate a multiplexed interface with endogenous cellular functions.

  17. The Cell Collective: Toward an open and collaborative approach to systems biology

    Directory of Open Access Journals (Sweden)

    Helikar Tomáš

    2012-08-01

    Full Text Available Abstract Background Despite decades of new discoveries in biomedical research, the overwhelming complexity of cells has been a significant barrier to a fundamental understanding of how cells work as a whole. As such, the holistic study of biochemical pathways requires computer modeling. Due to the complexity of cells, it is not feasible for one person or group to model the cell in its entirety. Results The Cell Collective is a platform that allows the world-wide scientific community to create these models collectively. Its interface enables users to build and use models without specifying any mathematical equations or computer code - addressing one of the major hurdles with computational research. In addition, this platform allows scientists to simulate and analyze the models in real-time on the web, including the ability to simulate loss/gain of function and test what-if scenarios in real time. Conclusions The Cell Collective is a web-based platform that enables laboratory scientists from across the globe to collaboratively build large-scale models of various biological processes, and simulate/analyze them in real time. In this manuscript, we show examples of its application to a large-scale model of signal transduction.

  18. Integrating cell biology and proteomic approaches in plants.

    Science.gov (United States)

    Takáč, Tomáš; Šamajová, Olga; Šamaj, Jozef

    2017-10-03

    Significant improvements of protein extraction, separation, mass spectrometry and bioinformatics nurtured advancements of proteomics during the past years. The usefulness of proteomics in the investigation of biological problems can be enhanced by integration with other experimental methods from cell biology, genetics, biochemistry, pharmacology, molecular biology and other omics approaches including transcriptomics and metabolomics. This review aims to summarize current trends integrating cell biology and proteomics in plant science. Cell biology approaches are most frequently used in proteomic studies investigating subcellular and developmental proteomes, however, they were also employed in proteomic studies exploring abiotic and biotic stress responses, vesicular transport, cytoskeleton and protein posttranslational modifications. They are used either for detailed cellular or ultrastructural characterization of the object subjected to proteomic study, validation of proteomic results or to expand proteomic data. In this respect, a broad spectrum of methods is employed to support proteomic studies including ultrastructural electron microscopy studies, histochemical staining, immunochemical localization, in vivo imaging of fluorescently tagged proteins and visualization of protein-protein interactions. Thus, cell biological observations on fixed or living cell compartments, cells, tissues and organs are feasible, and in some cases fundamental for the validation and complementation of proteomic data. Validation of proteomic data by independent experimental methods requires development of new complementary approaches. Benefits of cell biology methods and techniques are not sufficiently highlighted in current proteomic studies. This encouraged us to review most popular cell biology methods used in proteomic studies and to evaluate their relevance and potential for proteomic data validation and enrichment of purely proteomic analyses. We also provide examples of

  19. 11th International Conference on Practical Applications of Computational Biology & Bioinformatics

    CERN Document Server

    Mohamad, Mohd; Rocha, Miguel; Paz, Juan; Pinto, Tiago

    2017-01-01

    Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next-generation sequencing technologies, together with novel and constantly evolving, distinct types of omics data technologies, have created an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information and requires tools from the computational sciences. In the last few years, we have seen the rise of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. In this context, the interaction of r...

  20. 8th International Conference on Practical Applications of Computational Biology & Bioinformatics

    CERN Document Server

    Rocha, Miguel; Fdez-Riverola, Florentino; Santana, Juan

    2014-01-01

    Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researche...

  1. 10th International Conference on Practical Applications of Computational Biology & Bioinformatics

    CERN Document Server

    Rocha, Miguel; Fdez-Riverola, Florentino; Mayo, Francisco; Paz, Juan

    2016-01-01

    Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researche...

  2. The emerging age of cell-free synthetic biology.

    Science.gov (United States)

    Smith, Mark Thomas; Wilding, Kristen M; Hunt, Jeremy M; Bennett, Anthony M; Bundy, Bradley C

    2014-08-25

    The engineering of and mastery over biological parts has catalyzed the emergence of synthetic biology. This field has grown exponentially in the past decade. As increasingly more applications of synthetic biology are pursued, more challenges are encountered, such as delivering genetic material into cells and optimizing genetic circuits in vivo. An in vitro or cell-free approach to synthetic biology simplifies and avoids many of the pitfalls of in vivo synthetic biology. In this review, we describe some of the innate features that make cell-free systems compelling platforms for synthetic biology and discuss emerging improvements of cell-free technologies. We also select and highlight recent and emerging applications of cell-free synthetic biology. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  3. Analysis of undergraduate cell biology contents in Brazilian public universities.

    Science.gov (United States)

    Mermelstein, Claudia; Costa, Manoel Luis

    2017-04-01

    The enormous amount of information available in cell biology has created a challenge in selecting the core concepts we should be teaching our undergraduates. One way to define a set of essential core ideas in cell biology is to analyze what a specific cell biology community is teaching their students. Our main objective was to analyze the cell biology content currently being taught in Brazilian universities. We collected the syllabi of cell biology courses from public universities in Brazil and analyzed the frequency of cell biology topics in each course. We also compared the Brazilian data with the contents of a major cell biology textbook. Our analysis showed that while some cell biology topics such as plasma membrane and cytoskeleton was present in ∼100% of the Brazilian curricula analyzed others such as cell signaling and cell differentiation were present in only ∼35%. The average cell biology content taught in the Brazilian universities is quite different from what is presented in the textbook. We discuss several possible explanations for these observations. We also suggest a list with essential cell biology topics for any biological or biomedical undergraduate course. The comparative discussion of cell biology topics presented here could be valuable in other educational contexts. © 2017 The Authors. Cell Biology International Published by John Wiley & Sons Ltd on behalf of International Federation of Cell Biology.

  4. Notions of similarity for computational biology models

    KAUST Repository

    Waltemath, Dagmar

    2016-03-21

    Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of similarity may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here, we introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users\\' intuition about model similarity, and to support complex model searches in databases.

  5. Notions of similarity for computational biology models

    KAUST Repository

    Waltemath, Dagmar; Henkel, Ron; Hoehndorf, Robert; Kacprowski, Tim; Knuepfer, Christian; Liebermeister, Wolfram

    2016-01-01

    Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of similarity may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here, we introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users' intuition about model similarity, and to support complex model searches in databases.

  6. Proceedings of the first international conference on trends in cell and molecular biology: conference abstract book

    International Nuclear Information System (INIS)

    2015-01-01

    This conference throws light on topics for understanding the importance of nanotechnology as a potential treatment option for some important diseases. Computational biology with its vibrant research outputs needs to be integrated with modern cell biology as a whole to understand, analyze and predict the impacts in a much better way. Papers relevant to INIS are indexed separately

  7. 2nd Colombian Congress on Computational Biology and Bioinformatics

    CERN Document Server

    Cristancho, Marco; Isaza, Gustavo; Pinzón, Andrés; Rodríguez, Juan

    2014-01-01

    This volume compiles accepted contributions for the 2nd Edition of the Colombian Computational Biology and Bioinformatics Congress CCBCOL, after a rigorous review process in which 54 papers were accepted for publication from 119 submitted contributions. Bioinformatics and Computational Biology are areas of knowledge that have emerged due to advances that have taken place in the Biological Sciences and its integration with Information Sciences. The expansion of projects involving the study of genomes has led the way in the production of vast amounts of sequence data which needs to be organized, analyzed and stored to understand phenomena associated with living organisms related to their evolution, behavior in different ecosystems, and the development of applications that can be derived from this analysis.  .

  8. The ISCB Student Council Internship Program: Expanding computational biology capacity worldwide.

    Science.gov (United States)

    Anupama, Jigisha; Francescatto, Margherita; Rahman, Farzana; Fatima, Nazeefa; DeBlasio, Dan; Shanmugam, Avinash Kumar; Satagopam, Venkata; Santos, Alberto; Kolekar, Pandurang; Michaut, Magali; Guney, Emre

    2018-01-01

    Education and training are two essential ingredients for a successful career. On one hand, universities provide students a curriculum for specializing in one's field of study, and on the other, internships complement coursework and provide invaluable training experience for a fruitful career. Consequently, undergraduates and graduates are encouraged to undertake an internship during the course of their degree. The opportunity to explore one's research interests in the early stages of their education is important for students because it improves their skill set and gives their career a boost. In the long term, this helps to close the gap between skills and employability among students across the globe and balance the research capacity in the field of computational biology. However, training opportunities are often scarce for computational biology students, particularly for those who reside in less-privileged regions. Aimed at helping students develop research and academic skills in computational biology and alleviating the divide across countries, the Student Council of the International Society for Computational Biology introduced its Internship Program in 2009. The Internship Program is committed to providing access to computational biology training, especially for students from developing regions, and improving competencies in the field. Here, we present how the Internship Program works and the impact of the internship opportunities so far, along with the challenges associated with this program.

  9. The ISCB Student Council Internship Program: Expanding computational biology capacity worldwide.

    Directory of Open Access Journals (Sweden)

    Jigisha Anupama

    2018-01-01

    Full Text Available Education and training are two essential ingredients for a successful career. On one hand, universities provide students a curriculum for specializing in one's field of study, and on the other, internships complement coursework and provide invaluable training experience for a fruitful career. Consequently, undergraduates and graduates are encouraged to undertake an internship during the course of their degree. The opportunity to explore one's research interests in the early stages of their education is important for students because it improves their skill set and gives their career a boost. In the long term, this helps to close the gap between skills and employability among students across the globe and balance the research capacity in the field of computational biology. However, training opportunities are often scarce for computational biology students, particularly for those who reside in less-privileged regions. Aimed at helping students develop research and academic skills in computational biology and alleviating the divide across countries, the Student Council of the International Society for Computational Biology introduced its Internship Program in 2009. The Internship Program is committed to providing access to computational biology training, especially for students from developing regions, and improving competencies in the field. Here, we present how the Internship Program works and the impact of the internship opportunities so far, along with the challenges associated with this program.

  10. Physical Principles of Development of the State Standard of Biological Cell Polarizability

    Science.gov (United States)

    Shuvalov, G. V.; Generalov, K. V.; Generalov, V. M.; Kruchinina, M. V.; Koptev, E. S.; Minin, O. V.; Minin, I. V.

    2018-03-01

    A new state standard of biological cell polarizability based on micron-size latex particles has been developed. As a standard material, it is suggested to use polystyrene. Values of the polarizability calculated for erythrocytes and values of the polarizability of micron-size spherical latex particles measured with measuring-computing complexes agree within the limits of satisfactory relative error. The Standard allows one the unit of polarizability measurements [m3] to be assigned to cells and erythrocytes for the needs of medicine.

  11. Novel opportunities for computational biology and sociology in drug discovery☆

    Science.gov (United States)

    Yao, Lixia; Evans, James A.; Rzhetsky, Andrey

    2013-01-01

    Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development, explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy–industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies. PMID:20349528

  12. Novel opportunities for computational biology and sociology in drug discovery

    Science.gov (United States)

    Yao, Lixia

    2009-01-01

    Drug discovery today is impossible without sophisticated modeling and computation. In this review we touch on previous advances in computational biology and by tracing the steps involved in pharmaceutical development, we explore a range of novel, high value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry ties for scientific and human benefit. Attention to these opportunities could promise punctuated advance, and will complement the well-established computational work on which drug discovery currently relies. PMID:19674801

  13. Revision history aware repositories of computational models of biological systems.

    Science.gov (United States)

    Miller, Andrew K; Yu, Tommy; Britten, Randall; Cooling, Mike T; Lawson, James; Cowan, Dougal; Garny, Alan; Halstead, Matt D B; Hunter, Peter J; Nickerson, David P; Nunns, Geo; Wimalaratne, Sarala M; Nielsen, Poul M F

    2011-01-14

    Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs) for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. We have extended the Physiome Model Repository software to be fully revision history aware

  14. Revision history aware repositories of computational models of biological systems

    Directory of Open Access Journals (Sweden)

    Nickerson David P

    2011-01-01

    Full Text Available Abstract Background Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. Results We have extended the Physiome Model

  15. Computational brain models: Advances from system biology and future challenges

    Directory of Open Access Journals (Sweden)

    George E. Barreto

    2015-02-01

    Full Text Available Computational brain models focused on the interactions between neurons and astrocytes, modeled via metabolic reconstructions, are reviewed. The large source of experimental data provided by the -omics techniques and the advance/application of computational and data-management tools are being fundamental. For instance, in the understanding of the crosstalk between these cells, the key neuroprotective mechanisms mediated by astrocytes in specific metabolic scenarios (1 and the identification of biomarkers for neurodegenerative diseases (2,3. However, the modeling of these interactions demands a clear view of the metabolic and signaling pathways implicated, but most of them are controversial and are still under evaluation (4. Hence, to gain insight into the complexity of these interactions a current view of the main pathways implicated in the neuron-astrocyte communication processes have been made from recent experimental reports and reviews. Furthermore, target problems, limitations and main conclusions have been identified from metabolic models of the brain reported from 2010. Finally, key aspects to take into account into the development of a computational model of the brain and topics that could be approached from a systems biology perspective in future research are highlighted.

  16. Plant Systems Biology at the Single-Cell Level.

    Science.gov (United States)

    Libault, Marc; Pingault, Lise; Zogli, Prince; Schiefelbein, John

    2017-11-01

    Our understanding of plant biology is increasingly being built upon studies using 'omics and system biology approaches performed at the level of the entire plant, organ, or tissue. Although these approaches open new avenues to better understand plant biology, they suffer from the cellular complexity of the analyzed sample. Recent methodological advances now allow plant scientists to overcome this limitation and enable biological analyses of single-cells or single-cell-types. Coupled with the development of bioinformatics and functional genomics resources, these studies provide opportunities for high-resolution systems analyses of plant phenomena. In this review, we describe the recent advances, current challenges, and future directions in exploring the biology of single-cells and single-cell-types to enhance our understanding of plant biology as a system. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. A comprehensive approach to decipher biological computation to achieve next generation high-performance exascale computing.

    Energy Technology Data Exchange (ETDEWEB)

    James, Conrad D.; Schiess, Adrian B.; Howell, Jamie; Baca, Michael J.; Partridge, L. Donald; Finnegan, Patrick Sean; Wolfley, Steven L.; Dagel, Daryl James; Spahn, Olga Blum; Harper, Jason C.; Pohl, Kenneth Roy; Mickel, Patrick R.; Lohn, Andrew; Marinella, Matthew

    2013-10-01

    The human brain (volume=1200cm3) consumes 20W and is capable of performing > 10^16 operations/s. Current supercomputer technology has reached 1015 operations/s, yet it requires 1500m^3 and 3MW, giving the brain a 10^12 advantage in operations/s/W/cm^3. Thus, to reach exascale computation, two achievements are required: 1) improved understanding of computation in biological tissue, and 2) a paradigm shift towards neuromorphic computing where hardware circuits mimic properties of neural tissue. To address 1), we will interrogate corticostriatal networks in mouse brain tissue slices, specifically with regard to their frequency filtering capabilities as a function of input stimulus. To address 2), we will instantiate biological computing characteristics such as multi-bit storage into hardware devices with future computational and memory applications. Resistive memory devices will be modeled, designed, and fabricated in the MESA facility in consultation with our internal and external collaborators.

  18. Converting differential-equation models of biological systems to membrane computing.

    Science.gov (United States)

    Muniyandi, Ravie Chandren; Zin, Abdullah Mohd; Sanders, J W

    2013-12-01

    This paper presents a method to convert the deterministic, continuous representation of a biological system by ordinary differential equations into a non-deterministic, discrete membrane computation. The dynamics of the membrane computation is governed by rewrite rules operating at certain rates. That has the advantage of applying accurately to small systems, and to expressing rates of change that are determined locally, by region, but not necessary globally. Such spatial information augments the standard differentiable approach to provide a more realistic model. A biological case study of the ligand-receptor network of protein TGF-β is used to validate the effectiveness of the conversion method. It demonstrates the sense in which the behaviours and properties of the system are better preserved in the membrane computing model, suggesting that the proposed conversion method may prove useful for biological systems in particular. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  19. Dancing Styles of Collective Cell Migration: Image-Based Computational Analysis of JRAB/MICAL-L2.

    Science.gov (United States)

    Sakane, Ayuko; Yoshizawa, Shin; Yokota, Hideo; Sasaki, Takuya

    2018-01-01

    Collective cell migration is observed during morphogenesis, angiogenesis, and wound healing, and this type of cell migration also contributes to efficient metastasis in some kinds of cancers. Because collectively migrating cells are much better organized than a random assemblage of individual cells, there seems to be a kind of order in migrating clusters. Extensive research has identified a large number of molecules involved in collective cell migration, and these factors have been analyzed using dramatic advances in imaging technology. To date, however, it remains unclear how myriad cells are integrated as a single unit. Recently, we observed unbalanced collective cell migrations that can be likened to either precision dancing or awa-odori , Japanese traditional dancing similar to the style at Rio Carnival, caused by the impairment of the conformational change of JRAB/MICAL-L2. This review begins with a brief history of image-based computational analyses on cell migration, explains why quantitative analysis of the stylization of collective cell behavior is difficult, and finally introduces our recent work on JRAB/MICAL-L2 as a successful example of the multidisciplinary approach combining cell biology, live imaging, and computational biology. In combination, these methods have enabled quantitative evaluations of the "dancing style" of collective cell migration.

  20. Fundamentals of bioinformatics and computational biology methods and exercises in matlab

    CERN Document Server

    Singh, Gautam B

    2015-01-01

    This book offers comprehensive coverage of all the core topics of bioinformatics, and includes practical examples completed using the MATLAB bioinformatics toolbox™. It is primarily intended as a textbook for engineering and computer science students attending advanced undergraduate and graduate courses in bioinformatics and computational biology. The book develops bioinformatics concepts from the ground up, starting with an introductory chapter on molecular biology and genetics. This chapter will enable physical science students to fully understand and appreciate the ultimate goals of applying the principles of information technology to challenges in biological data management, sequence analysis, and systems biology. The first part of the book also includes a survey of existing biological databases, tools that have become essential in today’s biotechnology research. The second part of the book covers methodologies for retrieving biological information, including fundamental algorithms for sequence compar...

  1. Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective

    OpenAIRE

    Shuo Gu; Jianfeng Pei

    2017-01-01

    With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regula...

  2. Parallel metaheuristics in computational biology: an asynchronous cooperative enhanced scatter search method

    OpenAIRE

    Penas, David R.; González, Patricia; Egea, José A.; Banga, Julio R.; Doallo, Ramón

    2015-01-01

    Metaheuristics are gaining increased attention as efficient solvers for hard global optimization problems arising in bioinformatics and computational systems biology. Scatter Search (SS) is one of the recent outstanding algorithms in that class. However, its application to very hard problems, like those considering parameter estimation in dynamic models of systems biology, still results in excessive computation times. In order to reduce the computational cost of the SS and improve its success...

  3. Artificial cell mimics as simplified models for the study of cell biology.

    Science.gov (United States)

    Salehi-Reyhani, Ali; Ces, Oscar; Elani, Yuval

    2017-07-01

    Living cells are hugely complex chemical systems composed of a milieu of distinct chemical species (including DNA, proteins, lipids, and metabolites) interconnected with one another through a vast web of interactions: this complexity renders the study of cell biology in a quantitative and systematic manner a difficult task. There has been an increasing drive towards the utilization of artificial cells as cell mimics to alleviate this, a development that has been aided by recent advances in artificial cell construction. Cell mimics are simplified cell-like structures, composed from the bottom-up with precisely defined and tunable compositions. They allow specific facets of cell biology to be studied in isolation, in a simplified environment where control of variables can be achieved without interference from a living and responsive cell. This mini-review outlines the core principles of this approach and surveys recent key investigations that use cell mimics to address a wide range of biological questions. It will also place the field in the context of emerging trends, discuss the associated limitations, and outline future directions of the field. Impact statement Recent years have seen an increasing drive to construct cell mimics and use them as simplified experimental models to replicate and understand biological phenomena in a well-defined and controlled system. By summarizing the advances in this burgeoning field, and using case studies as a basis for discussion on the limitations and future directions of this approach, it is hoped that this minireview will spur others in the experimental biology community to use artificial cells as simplified models with which to probe biological systems.

  4. Introducing Mammalian Cell Culture and Cell Viability Techniques in the Undergraduate Biology Laboratory.

    Science.gov (United States)

    Bowey-Dellinger, Kristen; Dixon, Luke; Ackerman, Kristin; Vigueira, Cynthia; Suh, Yewseok K; Lyda, Todd; Sapp, Kelli; Grider, Michael; Crater, Dinene; Russell, Travis; Elias, Michael; Coffield, V McNeil; Segarra, Verónica A

    2017-01-01

    Undergraduate students learn about mammalian cell culture applications in introductory biology courses. However, laboratory modules are rarely designed to provide hands-on experience with mammalian cells or teach cell culture techniques, such as trypsinization and cell counting. Students are more likely to learn about cell culture using bacteria or yeast, as they are typically easier to grow, culture, and manipulate given the equipment, tools, and environment of most undergraduate biology laboratories. In contrast, the utilization of mammalian cells requires a dedicated biological safety cabinet and rigorous antiseptic techniques. For this reason, we have devised a laboratory module and method herein that familiarizes students with common cell culture procedures, without the use of a sterile hood or large cell culture facility. Students design and perform a time-efficient inquiry-based cell viability experiment using HeLa cells and tools that are readily available in an undergraduate biology laboratory. Students will become familiar with common techniques such as trypsinizing cells, cell counting with a hemocytometer, performing serial dilutions, and determining cell viability using trypan blue dye. Additionally, students will work with graphing software to analyze their data and think critically about the mechanism of death on a cellular level. Two different adaptations of this inquiry-based lab are presented-one for non-biology majors and one for biology majors. Overall, these laboratories aim to expose students to mammalian cell culture and basic techniques and help them to conceptualize their application in scientific research.

  5. Prion potency in stem cells biology.

    Science.gov (United States)

    Lopes, Marilene H; Santos, Tiago G

    2012-01-01

    Prion protein (PrP) can be considered a pivotal molecule because it interacts with several partners to perform a diverse range of critical biological functions that might differ in embryonic and adult cells. In recent years, there have been major advances in elucidating the putative role of PrP in the basic biology of stem cells in many different systems. Here, we review the evidence indicating that PrP is a key molecule involved in driving different aspects of the potency of embryonic and tissue-specific stem cells in self-perpetuation and differentiation in many cell types. It has been shown that PrP is involved in stem cell self-renewal, controlling pluripotency gene expression, proliferation, and neural and cardiomyocyte differentiation. PrP also has essential roles in distinct processes that regulate tissue-specific stem cell biology in nervous and hematopoietic systems and during muscle regeneration. Results from our own investigations have shown that PrP is able to modulate self-renewal and proliferation in neural stem cells, processes that are enhanced by PrP interactions with stress inducible protein 1 (STI1). Thus, the available data reveal the influence of PrP in acting upon the maintenance of pluripotent status or the differentiation of stem cells from the early embryogenesis through adulthood.

  6. ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus.

    Directory of Open Access Journals (Sweden)

    Peter D. Karp

    2015-01-01

    Full Text Available Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature, and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2,000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology [ISMB] 2016, Orlando, Florida.

  7. Cell biology experiments conducted in space

    Science.gov (United States)

    Taylor, G. R.

    1977-01-01

    A review of cell biology experiments conducted during the first two decades of space flight is provided. References are tabulated for work done with six types of living test system: isolated viruses, bacteriophage-host, bacteria, yeasts and filamentous fungi, protozoans, and small groups of cells (such as hamster cell tissue and fertilized frog eggs). The general results of studies involving the survival of cells in space, the effect of space flight on growing cultures, the biological effects of multicharged high-energy particles, and the effects of space flight on the genetic apparatus of microorganisms are summarized. It is concluded that cell systems remain sufficiently stable during space flight to permit experimentation with models requiring a fixed cell line during the space shuttle era.

  8. iTools: a framework for classification, categorization and integration of computational biology resources.

    Directory of Open Access Journals (Sweden)

    Ivo D Dinov

    2008-05-01

    Full Text Available The advancement of the computational biology field hinges on progress in three fundamental directions--the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources--data, software tools and web-services. The iTools design, implementation and resource meta-data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long

  9. Cell-free synthetic biology: thinking outside the cell.

    Science.gov (United States)

    Hodgman, C Eric; Jewett, Michael C

    2012-05-01

    Cell-free synthetic biology is emerging as a powerful approach aimed to understand, harness, and expand the capabilities of natural biological systems without using intact cells. Cell-free systems bypass cell walls and remove genetic regulation to enable direct access to the inner workings of the cell. The unprecedented level of control and freedom of design, relative to in vivo systems, has inspired the rapid development of engineering foundations for cell-free systems in recent years. These efforts have led to programmed circuits, spatially organized pathways, co-activated catalytic ensembles, rational optimization of synthetic multi-enzyme pathways, and linear scalability from the micro-liter to the 100-liter scale. It is now clear that cell-free systems offer a versatile test-bed for understanding why nature's designs work the way they do and also for enabling biosynthetic routes to novel chemicals, sustainable fuels, and new classes of tunable materials. While challenges remain, the emergence of cell-free systems is poised to open the way to novel products that until now have been impractical, if not impossible, to produce by other means. Copyright © 2011 Elsevier Inc. All rights reserved.

  10. Computational modeling of heterogeneity and function of CD4+ T cells

    Directory of Open Access Journals (Sweden)

    Adria eCarbo

    2014-07-01

    Full Text Available The immune system is composed of many different cell types and hundreds of intersecting molecular pathways and signals. This large biological complexity requires coordination between distinct pro-inflammatory and regulatory cell subsets to respond to infection while maintaining tissue homeostasis. CD4+ T cells play a central role in orchestrating immune responses and in maintaining a balance between pro- and anti- inflammatory responses. This tight balance between regulatory and effector reactions depends on the ability of CD4+ T cells to modulate distinct pathways within large molecular networks, since dysregulated CD4+ T cell responses may result in chronic inflammatory and autoimmune diseases. The CD4+ T cell differentiation process comprises an intricate interplay between cytokines, their receptors, adaptor molecules, signaling cascades and transcription factors that help delineate cell fate and function. Computational modeling can help to describe, simulate, analyze, and predict some of the behaviors in this complicated differentiation network. This review provides a comprehensive overview of existing computational immunology methods as well as novel strategies used to model immune responses with a particular focus on CD4+ T cell differentiation.

  11. Elastic Multi-scale Mechanisms: Computation and Biological Evolution.

    Science.gov (United States)

    Diaz Ochoa, Juan G

    2018-01-01

    Explanations based on low-level interacting elements are valuable and powerful since they contribute to identify the key mechanisms of biological functions. However, many dynamic systems based on low-level interacting elements with unambiguous, finite, and complete information of initial states generate future states that cannot be predicted, implying an increase of complexity and open-ended evolution. Such systems are like Turing machines, that overlap with dynamical systems that cannot halt. We argue that organisms find halting conditions by distorting these mechanisms, creating conditions for a constant creativity that drives evolution. We introduce a modulus of elasticity to measure the changes in these mechanisms in response to changes in the computed environment. We test this concept in a population of predators and predated cells with chemotactic mechanisms and demonstrate how the selection of a given mechanism depends on the entire population. We finally explore this concept in different frameworks and postulate that the identification of predictive mechanisms is only successful with small elasticity modulus.

  12. Biology of Schwann cells.

    Science.gov (United States)

    Kidd, Grahame J; Ohno, Nobuhiko; Trapp, Bruce D

    2013-01-01

    The fundamental roles of Schwann cells during peripheral nerve formation and regeneration have been recognized for more than 100 years, but the cellular and molecular mechanisms that integrate Schwann cell and axonal functions continue to be elucidated. Derived from the embryonic neural crest, Schwann cells differentiate into myelinating cells or bundle multiple unmyelinated axons into Remak fibers. Axons dictate which differentiation path Schwann cells follow, and recent studies have established that axonal neuregulin1 signaling via ErbB2/B3 receptors on Schwann cells is essential for Schwann cell myelination. Extracellular matrix production and interactions mediated by specific integrin and dystroglycan complexes are also critical requisites for Schwann cell-axon interactions. Myelination entails expansion and specialization of the Schwann cell plasma membrane over millimeter distances. Many of the myelin-specific proteins have been identified, and transgenic manipulation of myelin genes have provided novel insights into myelin protein function, including maintenance of axonal integrity and survival. Cellular events that facilitate myelination, including microtubule-based protein and mRNA targeting, and actin based locomotion, have also begun to be understood. Arguably, the most remarkable facet of Schwann cell biology, however, is their vigorous response to axonal damage. Degradation of myelin, dedifferentiation, division, production of axonotrophic factors, and remyelination all underpin the substantial regenerative capacity of the Schwann cells and peripheral nerves. Many of these properties are not shared by CNS fibers, which are myelinated by oligodendrocytes. Dissecting the molecular mechanisms responsible for the complex biology of Schwann cells continues to have practical benefits in identifying novel therapeutic targets not only for Schwann cell-specific diseases but other disorders in which axons degenerate. Copyright © 2013 Elsevier B.V. All rights

  13. Chaste: an open source C++ library for computational physiology and biology.

    KAUST Repository

    Mirams, Gary R; Arthurs, Christopher J; Bernabeu, Miguel O; Bordas, Rafel; Cooper, Jonathan; Corrias, Alberto; Davit, Yohan; Dunn, Sara-Jane; Fletcher, Alexander G; Harvey, Daniel G; Marsh, Megan E; Osborne, James M; Pathmanathan, Pras; Pitt-Francis, Joe; Southern, James; Zemzemi, Nejib; Gavaghan, David J

    2013-01-01

    Chaste - Cancer, Heart And Soft Tissue Environment - is an open source C++ library for the computational simulation of mathematical models developed for physiology and biology. Code development has been driven by two initial applications: cardiac electrophysiology and cancer development. A large number of cardiac electrophysiology studies have been enabled and performed, including high-performance computational investigations of defibrillation on realistic human cardiac geometries. New models for the initiation and growth of tumours have been developed. In particular, cell-based simulations have provided novel insight into the role of stem cells in the colorectal crypt. Chaste is constantly evolving and is now being applied to a far wider range of problems. The code provides modules for handling common scientific computing components, such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs). Re-use of these components avoids the need for researchers to 're-invent the wheel' with each new project, accelerating the rate of progress in new applications. Chaste is developed using industrially-derived techniques, in particular test-driven development, to ensure code quality, re-use and reliability. In this article we provide examples that illustrate the types of problems Chaste can be used to solve, which can be run on a desktop computer. We highlight some scientific studies that have used or are using Chaste, and the insights they have provided. The source code, both for specific releases and the development version, is available to download under an open source Berkeley Software Distribution (BSD) licence at http://www.cs.ox.ac.uk/chaste, together with details of a mailing list and links to documentation and tutorials.

  14. Chaste: an open source C++ library for computational physiology and biology.

    Directory of Open Access Journals (Sweden)

    Gary R Mirams

    Full Text Available Chaste - Cancer, Heart And Soft Tissue Environment - is an open source C++ library for the computational simulation of mathematical models developed for physiology and biology. Code development has been driven by two initial applications: cardiac electrophysiology and cancer development. A large number of cardiac electrophysiology studies have been enabled and performed, including high-performance computational investigations of defibrillation on realistic human cardiac geometries. New models for the initiation and growth of tumours have been developed. In particular, cell-based simulations have provided novel insight into the role of stem cells in the colorectal crypt. Chaste is constantly evolving and is now being applied to a far wider range of problems. The code provides modules for handling common scientific computing components, such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs. Re-use of these components avoids the need for researchers to 're-invent the wheel' with each new project, accelerating the rate of progress in new applications. Chaste is developed using industrially-derived techniques, in particular test-driven development, to ensure code quality, re-use and reliability. In this article we provide examples that illustrate the types of problems Chaste can be used to solve, which can be run on a desktop computer. We highlight some scientific studies that have used or are using Chaste, and the insights they have provided. The source code, both for specific releases and the development version, is available to download under an open source Berkeley Software Distribution (BSD licence at http://www.cs.ox.ac.uk/chaste, together with details of a mailing list and links to documentation and tutorials.

  15. Chaste: an open source C++ library for computational physiology and biology.

    KAUST Repository

    Mirams, Gary R

    2013-03-14

    Chaste - Cancer, Heart And Soft Tissue Environment - is an open source C++ library for the computational simulation of mathematical models developed for physiology and biology. Code development has been driven by two initial applications: cardiac electrophysiology and cancer development. A large number of cardiac electrophysiology studies have been enabled and performed, including high-performance computational investigations of defibrillation on realistic human cardiac geometries. New models for the initiation and growth of tumours have been developed. In particular, cell-based simulations have provided novel insight into the role of stem cells in the colorectal crypt. Chaste is constantly evolving and is now being applied to a far wider range of problems. The code provides modules for handling common scientific computing components, such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs). Re-use of these components avoids the need for researchers to \\'re-invent the wheel\\' with each new project, accelerating the rate of progress in new applications. Chaste is developed using industrially-derived techniques, in particular test-driven development, to ensure code quality, re-use and reliability. In this article we provide examples that illustrate the types of problems Chaste can be used to solve, which can be run on a desktop computer. We highlight some scientific studies that have used or are using Chaste, and the insights they have provided. The source code, both for specific releases and the development version, is available to download under an open source Berkeley Software Distribution (BSD) licence at http://www.cs.ox.ac.uk/chaste, together with details of a mailing list and links to documentation and tutorials.

  16. Laboratory of Cell and Molecular Biology

    Data.gov (United States)

    Federal Laboratory Consortium — The Laboratory of Cell and Molecular Biology investigates the organization, compartmentalization, and biochemistry of eukaryotic cells and the pathology associated...

  17. From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

    Science.gov (United States)

    Ross, Muriel D.

    1991-01-01

    The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

  18. Computational Biology and the Limits of Shared Vision

    DEFF Research Database (Denmark)

    Carusi, Annamaria

    2011-01-01

    of cases is necessary in order to gain a better perspective on social sharing of practices, and on what other factors this sharing is dependent upon. The article presents the case of currently emerging inter-disciplinary visual practices in the domain of computational biology, where the sharing of visual...... practices would be beneficial to the collaborations necessary for the research. Computational biology includes sub-domains where visual practices are coming to be shared across disciplines, and those where this is not occurring, and where the practices of others are resisted. A significant point......, its domain of study. Social practices alone are not sufficient to account for the shaping of evidence. The philosophy of Merleau-Ponty is introduced as providing an alternative framework for thinking of the complex inter-relations between all of these factors. This [End Page 300] philosophy enables us...

  19. Bioconductor: open software development for computational biology and bioinformatics

    DEFF Research Database (Denmark)

    Gentleman, R.C.; Carey, V.J.; Bates, D.M.

    2004-01-01

    The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisci......The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry...... into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples....

  20. Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective

    Directory of Open Access Journals (Sweden)

    Shuo Gu

    2017-01-01

    Full Text Available With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed.

  1. Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective.

    Science.gov (United States)

    Gu, Shuo; Pei, Jianfeng

    2017-01-01

    With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed.

  2. Glycoengineering in CHO cells: Advances in systems biology

    DEFF Research Database (Denmark)

    Tejwani, Vijay; Andersen, Mikael Rørdam; Nam, Jong Hyun

    2018-01-01

    are not well understood. A systems biology approach combining different technologies is needed for complete understanding of the molecular processes accounting for this variability and to open up new venues in cell line development. In this review, we describe several advances in genetic manipulation, modeling......For several decades, glycoprotein biologics have been successfully produced from Chinese hamster ovary (CHO) cells. The therapeutic efficacy and potency of glycoprotein biologics are often dictated by their post translational modifications, particularly glycosylation, which unlike protein synthesis....... Recently, CHO cells have also been explored for production of therapeutic glycosaminoglycans (e.g. heparin), which presents similar challenges as producing glycoproteins biologics. Approaches to controlling heterogeneity in CHO cells and directing the biosynthetic process toward desired glycoforms...

  3. XIV Mediterranean Conference on Medical and Biological Engineering and Computing

    CERN Document Server

    Christofides, Stelios; Pattichis, Constantinos

    2016-01-01

    This volume presents the proceedings of Medicon 2016, held in Paphos, Cyprus. Medicon 2016 is the XIV in the series of regional meetings of the International Federation of Medical and Biological Engineering (IFMBE) in the Mediterranean. The goal of Medicon 2016 is to provide updated information on the state of the art on Medical and Biological Engineering and Computing under the main theme “Systems Medicine for the Delivery of Better Healthcare Services”. Medical and Biological Engineering and Computing cover complementary disciplines that hold great promise for the advancement of research and development in complex medical and biological systems. Research and development in these areas are impacting the science and technology by advancing fundamental concepts in translational medicine, by helping us understand human physiology and function at multiple levels, by improving tools and techniques for the detection, prevention and treatment of disease. Medicon 2016 provides a common platform for the cross fer...

  4. Development and Implementation of Biological Circuits Using Excitable and Non-Excitable Cells

    Energy Technology Data Exchange (ETDEWEB)

    Casasnovas-Orus, V.; Gomez-Cid, L.; Hernandez-Romero, I.; Fuentes, L.; Guillem, M.S.; Atienza, F.; Fernandez-Aviles, F.; Climent, A.M.

    2016-07-01

    Compared to conventional computation systems, living beings require reduced power and raw materials consumption, inviting to explore the concept of biological circuits. In this project, a proof-of-concept of logical biocircuits using cell patterns has been developed. These were based upon differential ionic communication between cells, being the cells types used excitable and non-excitable, modeled by cardiomyocytes and fibroblasts correspondingly. To begin, patterns for the basic logic computation blocks were designed, including the OR gate, AND gate and logic memory. The designs were evaluated with mathematical models and in vitro experiments. Results of mathematical modeling indicated that theoretical approval of the biocircuit function. Regarding in vitro biocircuit implementation, three different selective cell localization techniques proved useful for the pattern creation. Evaluation with optical mapping confirmed the operation of the OR gate and logic memory. More resolution in the cell placement strategy will be needed to observe the proper AND gate operation. Thus, fine-tuning of the implementation process will enable the construction of more complex biocircuits that will take on clinical applications relating to electric stimulation of tissues and programmed drug delivery. (Author)

  5. Lipid Cell Biology: A Focus on Lipids in Cell Division.

    Science.gov (United States)

    Storck, Elisabeth M; Özbalci, Cagakan; Eggert, Ulrike S

    2018-06-20

    Cells depend on hugely diverse lipidomes for many functions. The actions and structural integrity of the plasma membrane and most organelles also critically depend on membranes and their lipid components. Despite the biological importance of lipids, our understanding of lipid engagement, especially the roles of lipid hydrophobic alkyl side chains, in key cellular processes is still developing. Emerging research has begun to dissect the importance of lipids in intricate events such as cell division. This review discusses how these structurally diverse biomolecules are spatially and temporally regulated during cell division, with a focus on cytokinesis. We analyze how lipids facilitate changes in cellular morphology during division and how they participate in key signaling events. We identify which cytokinesis proteins are associated with membranes, suggesting lipid interactions. More broadly, we highlight key unaddressed questions in lipid cell biology and techniques, including mass spectrometry, advanced imaging, and chemical biology, which will help us gain insights into the functional roles of lipids.

  6. Concise Review: Stem Cell Population Biology: Insights from Hematopoiesis.

    Science.gov (United States)

    MacLean, Adam L; Lo Celso, Cristina; Stumpf, Michael P H

    2017-01-01

    Stem cells are fundamental to human life and offer great therapeutic potential, yet their biology remains incompletely-or in cases even poorly-understood. The field of stem cell biology has grown substantially in recent years due to a combination of experimental and theoretical contributions: the experimental branch of this work provides data in an ever-increasing number of dimensions, while the theoretical branch seeks to determine suitable models of the fundamental stem cell processes that these data describe. The application of population dynamics to biology is amongst the oldest applications of mathematics to biology, and the population dynamics perspective continues to offer much today. Here we describe the impact that such a perspective has made in the field of stem cell biology. Using hematopoietic stem cells as our model system, we discuss the approaches that have been used to study their key properties, such as capacity for self-renewal, differentiation, and cell fate lineage choice. We will also discuss the relevance of population dynamics in models of stem cells and cancer, where competition naturally emerges as an influential factor on the temporal evolution of cell populations. Stem Cells 2017;35:80-88. © 2016 AlphaMed Press.

  7. Two- and three-input TALE-based AND logic computation in embryonic stem cells.

    Science.gov (United States)

    Lienert, Florian; Torella, Joseph P; Chen, Jan-Hung; Norsworthy, Michael; Richardson, Ryan R; Silver, Pamela A

    2013-11-01

    Biological computing circuits can enhance our ability to control cellular functions and have potential applications in tissue engineering and medical treatments. Transcriptional activator-like effectors (TALEs) represent attractive components of synthetic gene regulatory circuits, as they can be designed de novo to target a given DNA sequence. We here demonstrate that TALEs can perform Boolean logic computation in mammalian cells. Using a split-intein protein-splicing strategy, we show that a functional TALE can be reconstituted from two inactive parts, thus generating two-input AND logic computation. We further demonstrate three-piece intein splicing in mammalian cells and use it to perform three-input AND computation. Using methods for random as well as targeted insertion of these relatively large genetic circuits, we show that TALE-based logic circuits are functional when integrated into the genome of mouse embryonic stem cells. Comparing construct variants in the same genomic context, we modulated the strength of the TALE-responsive promoter to improve the output of these circuits. Our work establishes split TALEs as a tool for building logic computation with the potential of controlling expression of endogenous genes or transgenes in response to a combination of cellular signals.

  8. Micro/nano-fabrication technologies for cell biology.

    Science.gov (United States)

    Qian, Tongcheng; Wang, Yingxiao

    2010-10-01

    Micro/nano-fabrication techniques, such as soft lithography and electrospinning, have been well-developed and widely applied in many research fields in the past decade. Due to the low costs and simple procedures, these techniques have become important and popular for biological studies. In this review, we focus on the studies integrating micro/nano-fabrication work to elucidate the molecular mechanism of signaling transduction in cell biology. We first describe different micro/nano-fabrication technologies, including techniques generating three-dimensional scaffolds for tissue engineering. We then introduce the application of these technologies in manipulating the physical or chemical micro/nano-environment to regulate the cellular behavior and response, such as cell life and death, differentiation, proliferation, and cell migration. Recent advancement in integrating the micro/nano-technologies and live cell imaging are also discussed. Finally, potential schemes in cell biology involving micro/nano-fabrication technologies are proposed to provide perspectives on the future research activities.

  9. Computed tomography of cryogenic cells

    International Nuclear Information System (INIS)

    Schneider, Gerd; Anderson, E.; Vogt, S.; Knochel, C.; Weiss, D.; LeGros, M.; Larabell, C.

    2001-01-01

    Due to the short wavelengths of X-rays and low numerical aperture of the Fresnel zone plates used as X-ray objectives, the depth of field is several microns. Within the focal depth, imaging a thick specimen is to a good approximation equivalent to projecting the specimen absorption. Therefore, computed tomography based on a tilt series of X-ray microscopic images can be used to reconstruct the local linear absorption coefficient and image the three-dimensional specimen structure. To preserve the structural integrity of biological objects during image acquisition, microscopy is performed at cryogenic temperatures. Tomography based on X-ray microscopic images was applied to study the distribution of male specific lethal 1 (MSL-1), a nuclear protein involved in dosage compensation in Drosophila melanogaster, which ensures that males with single X chromosome have the same amount of most X-linked gene products as females with two X chromosomes. Tomographic reconstructions of X-ray microscopic images were used to compute the local three-dimensional linear absorption coefficient revealing the arrangement of internal structures of Drosophila melanogaster cells. Combined with labelling techniques, nanotomography is a new technique to study the 3D distribution of selected proteins inside whole cells. We want to improve this technique with respect to resolution and specimen preparation. The resolution in the reconstruction can be significantly improved by reducing the angular step size to collect more viewing angles, which requires an automated data acquisition. In addition, fast-freezing with liquid ethane instead of cryogenic He gas will be applied to improve the vitrification of the hydrated samples. We also plan to apply cryo X-ray nanotomography in order to study different types of cells and their nuclear protein distributions

  10. Systems biology of stored blood cells: can it help to extend the expiration date?

    Science.gov (United States)

    Paglia, Giuseppe; Palsson, Bernhard Ø; Sigurjonsson, Olafur E

    2012-12-05

    With increasingly stringent regulations regarding deferral and elimination of blood donors it will become increasingly important to extend the expiration date of blood components beyond the current allowed storage periods. One reason for the storage time limit for blood components is that platelets and red blood cells develop a condition called storage lesions during their storage in plastic blood containers. Systems biology provides comprehensive bio-chemical descriptions of organisms through quantitative measurements and data integration in mathematical models. The biological knowledge for a target organism can be translated in a mathematical format and used to compute physiological properties. The use of systems biology represents a concrete solution in the study of blood cell storage lesions, and it may open up new avenues towards developing better storage methods and better storage media, thereby extending the storage period of blood components. This article is part of a Special Issue entitled: Integrated omics. Copyright © 2012 Elsevier B.V. All rights reserved.

  11. Modeling biological problems in computer science: a case study in genome assembly.

    Science.gov (United States)

    Medvedev, Paul

    2018-01-30

    As computer scientists working in bioinformatics/computational biology, we often face the challenge of coming up with an algorithm to answer a biological question. This occurs in many areas, such as variant calling, alignment and assembly. In this tutorial, we use the example of the genome assembly problem to demonstrate how to go from a question in the biological realm to a solution in the computer science realm. We show the modeling process step-by-step, including all the intermediate failed attempts. Please note this is not an introduction to how genome assembly algorithms work and, if treated as such, would be incomplete and unnecessarily long-winded. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  12. Computational properties of mitochondria in T cell activation and fate.

    Science.gov (United States)

    Uzhachenko, Roman; Shanker, Anil; Dupont, Geneviève

    2016-11-01

    In this article, we review how mitochondrial Ca 2+ transport (mitochondrial Ca 2+ uptake and Na + /Ca 2+ exchange) is involved in T cell biology, including activation and differentiation through shaping cellular Ca 2+ signals. Based on recent observations, we propose that the Ca 2+ crosstalk between mitochondria, endoplasmic reticulum and cytoplasm may form a proportional-integral-derivative (PID) controller. This PID mechanism (which is well known in engineering) could be responsible for computing cellular decisions. In addition, we point out the importance of analogue and digital signal processing in T cell life and implication of mitochondrial Ca 2+ transport in this process. © 2016 The Authors.

  13. Three-dimensional printing of human skeletal muscle cells: An interdisciplinary approach for studying biological systems.

    Science.gov (United States)

    Bagley, James R; Galpin, Andrew J

    2015-01-01

    Interdisciplinary exploration is vital to education in the 21st century. This manuscript outlines an innovative laboratory-based teaching method that combines elements of biochemistry/molecular biology, kinesiology/health science, computer science, and manufacturing engineering to give students the ability to better conceptualize complex biological systems. Here, we utilize technology available at most universities to print three-dimensional (3D) scale models of actual human muscle cells (myofibers) out of bioplastic materials. The same methodological approach could be applied to nearly any cell type or molecular structure. This advancement is significant because historically, two-dimensional (2D) myocellular images have proven insufficient for detailed analysis of organelle organization and morphology. 3D imaging fills this void by providing accurate and quantifiable myofiber structural data. Manipulating tangible 3D models combats 2D limitation and gives students new perspectives and alternative learning experiences that may assist their understanding. This approach also exposes learners to 1) human muscle cell extraction and isolation, 2) targeted fluorescence labeling, 3) confocal microscopy, 4) image processing (via open-source software), and 5) 3D printing bioplastic scale-models (×500 larger than the actual cells). Creating these physical models may further student's interest in the invisible world of molecular and cellular biology. Furthermore, this interdisciplinary laboratory project gives instructors of all biological disciplines a new teaching tool to foster integrative thinking. © 2015 The International Union of Biochemistry and Molecular Biology.

  14. Computational intelligence, medicine and biology selected links

    CERN Document Server

    Zaitseva, Elena

    2015-01-01

    This book contains an interesting and state-of the art collection of chapters presenting several examples of attempts to developing modern tools utilizing computational intelligence in different real life problems encountered by humans. Reasoning, prediction, modeling, optimization, decision making, etc. need modern, soft and intelligent algorithms, methods and methodologies to solve, in the efficient ways, problems appearing in human activity. The contents of the book is divided into two parts. Part I, consisting of four chapters, is devoted to selected links of computational intelligence, medicine, health care and biomechanics. Several problems are considered: estimation of healthcare system reliability, classification of ultrasound thyroid images, application of fuzzy logic to measure weight status and central fatness, and deriving kinematics directly from video records. Part II, also consisting of four chapters, is devoted to selected links of computational intelligence and biology. The common denominato...

  15. Using a Computer Animation to Teach High School Molecular Biology

    Science.gov (United States)

    Rotbain, Yosi; Marbach-Ad, Gili; Stavy, Ruth

    2008-01-01

    We present an active way to use a computer animation in secondary molecular genetics class. For this purpose we developed an activity booklet that helps students to work interactively with a computer animation which deals with abstract concepts and processes in molecular biology. The achievements of the experimental group were compared with those…

  16. Synthetic biology approaches to engineer T cells.

    Science.gov (United States)

    Wu, Chia-Yung; Rupp, Levi J; Roybal, Kole T; Lim, Wendell A

    2015-08-01

    There is rapidly growing interest in learning how to engineer immune cells, such as T lymphocytes, because of the potential of these engineered cells to be used for therapeutic applications such as the recognition and killing of cancer cells. At the same time, our knowhow and capability to logically engineer cellular behavior is growing rapidly with the development of synthetic biology. Here we describe how synthetic biology approaches are being used to rationally alter the behavior of T cells to optimize them for therapeutic functions. We also describe future developments that will be important in order to construct safe and precise T cell therapeutics. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Electromagnetic effects - From cell biology to medicine.

    Science.gov (United States)

    Funk, Richard H W; Monsees, Thomas; Ozkucur, Nurdan

    2009-01-01

    In this review we compile and discuss the published plethora of cell biological effects which are ascribed to electric fields (EF), magnetic fields (MF) and electromagnetic fields (EMF). In recent years, a change in paradigm took place concerning the endogenously produced static EF of cells and tissues. Here, modern molecular biology could link the action of ion transporters and ion channels to the "electric" action of cells and tissues. Also, sensing of these mainly EF could be demonstrated in studies of cell migration and wound healing. The triggers exerted by ion concentrations and concomitant electric field gradients have been traced along signaling cascades till gene expression changes in the nucleus. Far more enigmatic is the way of action of static MF which come in most cases from outside (e.g. earth magnetic field). All systems in an organism from the molecular to the organ level are more or less in motion. Thus, in living tissue we mostly find alternating fields as well as combination of EF and MF normally in the range of extremely low-frequency EMF. Because a bewildering array of model systems and clinical devices exits in the EMF field we concentrate on cell biological findings and look for basic principles in the EF, MF and EMF action. As an outlook for future research topics, this review tries to link areas of EF, MF and EMF research to thermodynamics and quantum physics, approaches that will produce novel insights into cell biology.

  18. An experimental and computational framework to build a dynamic protein atlas of human cell division

    OpenAIRE

    Kavur, Marina; Kavur, Marina; Kavur, Marina; Ellenberg, Jan; Peters, Jan-Michael; Ladurner, Rene; Martinic, Marina; Kueblbeck, Moritz; Nijmeijer, Bianca; Wachsmuth, Malte; Koch, Birgit; Walther, Nike; Politi, Antonio; Heriche, Jean-Karim; Hossain, M.

    2017-01-01

    Essential biological functions of human cells, such as division, require the tight coordination of the activity of hundreds of proteins in space and time. While live cell imaging is a powerful tool to study the distribution and dynamics of individual proteins after fluorescence tagging, it has not yet been used to map protein networks due to the lack of systematic and quantitative experimental and computational approaches. Using the cell and nuclear boundaries as landmarks, we generated a 4D ...

  19. Seeing Cells: Teaching the Visual/Verbal Rhetoric of Biology

    Science.gov (United States)

    Dinolfo, John; Heifferon, Barbara; Temesvari, Lesly A.

    2007-01-01

    This pilot study obtained baseline information on verbal and visual rhetorics to teach microscopy techniques to college biology majors. We presented cell images to students in cell biology and biology writing classes and then asked them to identify textual, verbal, and visual cues that support microscopy learning. Survey responses suggest that…

  20. Mammalian cell biology

    International Nuclear Information System (INIS)

    Anon.

    1976-01-01

    Progress is reported on studies of the molecular biology and functional changes in cultured mammalian cells following exposure to x radiation, uv radiation, fission neutrons, or various chemical environmental pollutants alone or in combinations. Emphasis was placed on the separate and combined effects of polycyclic aromatic hydrocarbons released during combustion of fossil fuels and ionizing and nonionizing radiations. Sun lamps, which emit a continuous spectrum of near ultraviolet light of 290 nm to 315 nm were used for studies of predictive cell killing due to sunlight. Results showed that exposure to uv light (254 nm) may not be adequate to predict effects produced by sunlight. Data are included from studies on single-strand breaks and repair in DNA of cultured hamster cells exposed to uv or nearultraviolet light. The possible interactions of the polycyclic aromatic hydrocarbon 7,12-dimethylbenz(a)-anthracene (DmBA) alone or combined with exposure to x radiation, uv radiation (254 nm) or near ultraviolet simulating sunlight were compared for effects on cell survival

  1. Cell biology of the Koji mold Aspergillus oryzae.

    Science.gov (United States)

    Kitamoto, Katsuhiko

    2015-01-01

    Koji mold, Aspergillus oryzae, has been used for the production of sake, miso, and soy sauce for more than one thousand years in Japan. Due to the importance, A. oryzae has been designated as the national micro-organism of Japan (Koku-kin). A. oryzae has been intensively studied in the past century, with most investigations focusing on breeding techniques and developing methods for Koji making for sake brewing. However, the understanding of fundamental biology of A. oryzae remains relatively limited compared with the yeast Saccharomyces cerevisiae. Therefore, we have focused on studying the cell biology including live cell imaging of organelles, protein vesicular trafficking, autophagy, and Woronin body functions using the available genomic information. In this review, I describe essential findings of cell biology of A. oryzae obtained in our study for a quarter of century. Understanding of the basic biology will be critical for not its biotechnological application, but also for an understanding of the fundamental biology of other filamentous fungi.

  2. Potentials of single-cell biology in identification and validation of disease biomarkers.

    Science.gov (United States)

    Niu, Furong; Wang, Diane C; Lu, Jiapei; Wu, Wei; Wang, Xiangdong

    2016-09-01

    Single-cell biology is considered a new approach to identify and validate disease-specific biomarkers. However, the concern raised by clinicians is how to apply single-cell measurements for clinical practice, translate the message of single-cell systems biology into clinical phenotype or explain alterations of single-cell gene sequencing and function in patient response to therapies. This study is to address the importance and necessity of single-cell gene sequencing in the identification and development of disease-specific biomarkers, the definition and significance of single-cell biology and single-cell systems biology in the understanding of single-cell full picture, the development and establishment of whole-cell models in the validation of targeted biological function and the figure and meaning of single-molecule imaging in single cell to trace intra-single-cell molecule expression, signal, interaction and location. We headline the important role of single-cell biology in the discovery and development of disease-specific biomarkers with a special emphasis on understanding single-cell biological functions, e.g. mechanical phenotypes, single-cell biology, heterogeneity and organization of genome function. We have reason to believe that such multi-dimensional, multi-layer, multi-crossing and stereoscopic single-cell biology definitely benefits the discovery and development of disease-specific biomarkers. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

  3. Tomography studies of biological cells on polymer scaffolds

    International Nuclear Information System (INIS)

    Thurner, P; Mueller, B; Sennhauser, U; Hubbell, J; Mueller, R

    2004-01-01

    Advances in cell biology and tissue engineering rely heavily on performing 2D cell culture experiments. Analysis of these is conventionally done with 2D imaging techniques such as light (LM) or electron microscopy (SEM), since they are readily available. Cells, however, might act significantly differently when cultured in 2D or 3D environments. In order to analyse cells in a 3D arrangement, new imaging techniques are necessary not only in order to visualize the periphery of the cell culture in reflection mode but also to perform qualitative and quantitative investigations of the inner parts. Synchrotron radiation micro-computed tomography (SRμCT) using hard x-rays was shown to be a promising tool that can be used for 3D cell culture visualization. SRμCT allows not only visualization of cell cultures in their native 3D environment but also use of the volumetric nature of this imaging procedure to evaluate the cells quantitatively. In our approach, cells were seeded on polymer yarns, stained and measured with SRμCT in absorption and in differential absorption contrast mode. A new segmentation procedure was developed and the measured volumetric data were quantitatively assessed. Quantification parameters included total cell volume, total yarn volume, cell volume density, which is the ratio of cell to yarn volume, and the radial cell mass distribution. The applied variation of the staining parameter of gold enhancement incubation time was shown to have significant influence on the cell volume density. Differential absorption contrast mode was found to provide similar but no additional information on the investigated sample. Using novel approaches of hierarchical volumetric imaging allows closure of the gap between imaging of whole organs and single cells and might be expanded to even higher resolutions, offering investigation of the cell machinery in closer detail

  4. Molecular biology of the cell

    National Research Council Canada - National Science Library

    Alberts, Bruce; Walter, Peter; Raff, Martin; Roberts, Keith; Lewis, Julian; Johnson, Alexander

    2007-01-01

    .... By extracting fundamental concepts and meaning from this enormous and ever-growing field, the authors tell the story of cell biology, and create a coherent framework through which non-expert readers...

  5. A comparative approach for the investigation of biological information processing: An examination of the structure and function of computer hard drives and DNA

    Science.gov (United States)

    2010-01-01

    Background The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Methods Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Results Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological

  6. A comparative approach for the investigation of biological information processing: an examination of the structure and function of computer hard drives and DNA.

    Science.gov (United States)

    D'Onofrio, David J; An, Gary

    2010-01-21

    The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological systems do not have an

  7. A comparative approach for the investigation of biological information processing: An examination of the structure and function of computer hard drives and DNA

    Directory of Open Access Journals (Sweden)

    D'Onofrio David J

    2010-01-01

    Full Text Available Abstract Background The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Methods Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1 orthogonal uniqueness, (2 low level formatting, (3 high level formatting and (4 translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Results Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT during high level formatting of the computer hard drive and the subsequent loading of an operating

  8. Cell-free synthetic biology for environmental sensing and remediation.

    Science.gov (United States)

    Karig, David K

    2017-06-01

    The fields of biosensing and bioremediation leverage the phenomenal array of sensing and metabolic capabilities offered by natural microbes. Synthetic biology provides tools for transforming these fields through complex integration of natural and novel biological components to achieve sophisticated sensing, regulation, and metabolic function. However, the majority of synthetic biology efforts are conducted in living cells, and concerns over releasing genetically modified organisms constitute a key barrier to environmental applications. Cell-free protein expression systems offer a path towards leveraging synthetic biology, while preventing the spread of engineered organisms in nature. Recent efforts in the areas of cell-free approaches for sensing, regulation, and metabolic pathway implementation, as well as for preserving and deploying cell-free expression components, embody key steps towards realizing the potential of cell-free systems for environmental sensing and remediation. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.

  9. Biological interaction of living cells with COSAN-based synthetic vesicles.

    Science.gov (United States)

    Tarrés, Màrius; Canetta, Elisabetta; Paul, Eleanor; Forbes, Jordan; Azzouni, Karima; Viñas, Clara; Teixidor, Francesc; Harwood, Adrian J

    2015-01-15

    Cobaltabisdicarbollide (COSAN) [3,3'-Co(1,2-C2B9H11)2](-), is a complex boron-based anion that has the unusual property of self-assembly into membranes and vesicles. These membranes have similar dimensions to biological membranes found in cells, and previously COSAN has been shown to pass through synthetic lipid membranes and those of living cells without causing breakdown of membrane barrier properties. Here, we investigate the interaction of this inorganic membrane system with living cells. We show that COSAN has no immediate effect on cell viability, and cells fully recover when COSAN is removed following exposure for hours to days. COSAN elicits a range of cell biological effects, including altered cell morphology, inhibition of cell growth and, in some cases, apoptosis. These observations reveal a new biology at the interface between inorganic, synthetic COSAN membranes and naturally occurring biological membranes.

  10. A computational approach for inferring the cell wall properties that govern guard cell dynamics.

    Science.gov (United States)

    Woolfenden, Hugh C; Bourdais, Gildas; Kopischke, Michaela; Miedes, Eva; Molina, Antonio; Robatzek, Silke; Morris, Richard J

    2017-10-01

    Guard cells dynamically adjust their shape in order to regulate photosynthetic gas exchange, respiration rates and defend against pathogen entry. Cell shape changes are determined by the interplay of cell wall material properties and turgor pressure. To investigate this relationship between turgor pressure, cell wall properties and cell shape, we focused on kidney-shaped stomata and developed a biomechanical model of a guard cell pair. Treating the cell wall as a composite of the pectin-rich cell wall matrix embedded with cellulose microfibrils, we show that strong, circumferentially oriented fibres are critical for opening. We find that the opening dynamics are dictated by the mechanical stress response of the cell wall matrix, and as the turgor rises, the pectinaceous matrix stiffens. We validate these predictions with stomatal opening experiments in selected Arabidopsis cell wall mutants. Thus, using a computational framework that combines a 3D biomechanical model with parameter optimization, we demonstrate how to exploit subtle shape changes to infer cell wall material properties. Our findings reveal that proper stomatal dynamics are built on two key properties of the cell wall, namely anisotropy in the form of hoop reinforcement and strain stiffening. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd and Society for Experimental Biology.

  11. Simulation of CNT-AFM tip based on finite element analysis for targeted probe of the biological cell

    Energy Technology Data Exchange (ETDEWEB)

    Yousefi, Amin Termeh, E-mail: at.tyousefi@gmail.com; Miyake, Mikio, E-mail: miyakejaist@gmail.com; Ikeda, Shoichiro, E-mail: sho16.ikeda@gmail.com [ChECA IKohza, Dept. Environmental & Green Technology (EGT), Malaysia, Japan International Institute of Technology (MJIIT), University Technology Malaysia - UTM, Kualalumpur (Malaysia); Mahmood, Mohamad Rusop, E-mail: nano@uitm.gmail.com [NANO-SciTech Centre, Institute of Science, Universiti Teknologi MARA (UiTM), Shah Alam, Selangor (Malaysia)

    2016-07-06

    Carbon nanotubes (CNTs) are potentially ideal tips for atomic force microscopy (AFM) due to the robust mechanical properties, nano scale diameter and also their ability to be functionalized by chemical and biological components at the tip ends. This contribution develops the idea of using CNTs as an AFM tip in computational analysis of the biological cell’s. Finite element analysis employed for each section and displacement of the nodes located in the contact area was monitored by using an output database (ODB). This reliable integration of CNT-AFM tip process provides a new class of high performance nanoprobes for single biological cell analysis.

  12. Stochastic processes in cell biology

    CERN Document Server

    Bressloff, Paul C

    2014-01-01

    This book develops the theory of continuous and discrete stochastic processes within the context of cell biology.  A wide range of biological topics are covered including normal and anomalous diffusion in complex cellular environments, stochastic ion channels and excitable systems, stochastic calcium signaling, molecular motors, intracellular transport, signal transduction, bacterial chemotaxis, robustness in gene networks, genetic switches and oscillators, cell polarization, polymerization, cellular length control, and branching processes. The book also provides a pedagogical introduction to the theory of stochastic process – Fokker Planck equations, stochastic differential equations, master equations and jump Markov processes, diffusion approximations and the system size expansion, first passage time problems, stochastic hybrid systems, reaction-diffusion equations, exclusion processes, WKB methods, martingales and branching processes, stochastic calculus, and numerical methods.   This text is primarily...

  13. Filling the gap between biology and computer science.

    Science.gov (United States)

    Aguilar-Ruiz, Jesús S; Moore, Jason H; Ritchie, Marylyn D

    2008-07-17

    This editorial introduces BioData Mining, a new journal which publishes research articles related to advances in computational methods and techniques for the extraction of useful knowledge from heterogeneous biological data. We outline the aims and scope of the journal, introduce the publishing model and describe the open peer review policy, which fosters interaction within the research community.

  14. Mast cells: potential positive and negative roles in tumor biology.

    Science.gov (United States)

    Marichal, Thomas; Tsai, Mindy; Galli, Stephen J

    2013-11-01

    Mast cells are immune cells that reside in virtually all vascularized tissues. Upon activation by diverse mechanisms, mast cells can secrete a broad array of biologically active products that either are stored in the cytoplasmic granules of the cells (e.g., histamine, heparin, various proteases) or are produced de novo upon cell stimulation (e.g., prostaglandins, leukotrienes, cytokines, chemokines, and growth factors). Mast cells are best known for their effector functions during anaphylaxis and acute IgE-associated allergic reactions, but they also have been implicated in a wide variety of processes that maintain health or contribute to disease. There has been particular interest in the possible roles of mast cells in tumor biology. In vitro studies have shown that mast cells have the potential to influence many aspects of tumor biology, including tumor development, tumor-induced angiogenesis, and tissue remodeling, and the shaping of adaptive immune responses to tumors. Yet, the actual contributions of mast cells to tumor biology in vivo remain controversial. Here, we review some basic features of mast cell biology with a special emphasis on those relevant to their potential roles in tumors. We discuss how using in vivo tumor models in combination with models in which mast cell function can be modulated has implicated mast cells in the regulation of host responses to tumors. Finally, we summarize data from studies of human tumors that suggest either beneficial or detrimental roles for mast cells in tumors. ©2013 AACR.

  15. Regenerative patterning in Swarm Robots: mutual benefits of research in robotics and stem cell biology

    Science.gov (United States)

    RUBENSTEIN, MICHAEL; SAI, YING; CHUONG, CHENG-MING; SHEN, WEI-MIN

    2010-01-01

    This paper presents a novel perspective of Robotic Stem Cells (RSCs), defined as the basic non-biological elements with stem cell like properties that can self-reorganize to repair damage to their swarming organization. “Self” here means that the elements can autonomously decide and execute their actions without requiring any preset triggers, commands, or help from external sources. We develop this concept for two purposes. One is to develop a new theory for self-organization and self-assembly of multi-robots systems that can detect and recover from unforeseen errors or attacks. This self-healing and self-regeneration is used to minimize the compromise of overall function for the robot team. The other is to decipher the basic algorithms of regenerative behaviors in multi-cellular animal models, so that we can understand the fundamental principles used in the regeneration of biological systems. RSCs are envisioned to be basic building elements for future systems that are capable of self-organization, self-assembly, self-healing and self-regeneration. We first discuss the essential features of biological stem cells for such a purpose, and then propose the functional requirements of robotic stem cells with properties equivalent to gene controller, program selector and executor. We show that RSCs are a novel robotic model for scalable self-organization and self-healing in computer simulations and physical implementation. As our understanding of stem cells advances, we expect that future robots will be more versatile, resilient and complex, and such new robotic systems may also demand and inspire new knowledge from stem cell biology and related fields, such as artificial intelligence and tissue engineering. PMID:19557691

  16. Regenerative patterning in Swarm Robots: mutual benefits of research in robotics and stem cell biology.

    Science.gov (United States)

    Rubenstein, Michael; Sai, Ying; Chuong, Cheng-Ming; Shen, Wei-Min

    2009-01-01

    This paper presents a novel perspective of Robotic Stem Cells (RSCs), defined as the basic non-biological elements with stem cell like properties that can self-reorganize to repair damage to their swarming organization. Self here means that the elements can autonomously decide and execute their actions without requiring any preset triggers, commands, or help from external sources. We develop this concept for two purposes. One is to develop a new theory for self-organization and self-assembly of multi-robots systems that can detect and recover from unforeseen errors or attacks. This self-healing and self-regeneration is used to minimize the compromise of overall function for the robot team. The other is to decipher the basic algorithms of regenerative behaviors in multi-cellular animal models, so that we can understand the fundamental principles used in the regeneration of biological systems. RSCs are envisioned to be basic building elements for future systems that are capable of self-organization, self-assembly, self-healing and self-regeneration. We first discuss the essential features of biological stem cells for such a purpose, and then propose the functional requirements of robotic stem cells with properties equivalent to gene controller, program selector and executor. We show that RSCs are a novel robotic model for scalable self-organization and self-healing in computer simulations and physical implementation. As our understanding of stem cells advances, we expect that future robots will be more versatile, resilient and complex, and such new robotic systems may also demand and inspire new knowledge from stem cell biology and related fields, such as artificial intelligence and tissue engineering.

  17. MACBenAbim: A Multi-platform Mobile Application for searching keyterms in Computational Biology and Bioinformatics.

    Science.gov (United States)

    Oluwagbemi, Olugbenga O; Adewumi, Adewole; Esuruoso, Abimbola

    2012-01-01

    Computational biology and bioinformatics are gradually gaining grounds in Africa and other developing nations of the world. However, in these countries, some of the challenges of computational biology and bioinformatics education are inadequate infrastructures, and lack of readily-available complementary and motivational tools to support learning as well as research. This has lowered the morale of many promising undergraduates, postgraduates and researchers from aspiring to undertake future study in these fields. In this paper, we developed and described MACBenAbim (Multi-platform Mobile Application for Computational Biology and Bioinformatics), a flexible user-friendly tool to search for, define and describe the meanings of keyterms in computational biology and bioinformatics, thus expanding the frontiers of knowledge of the users. This tool also has the capability of achieving visualization of results on a mobile multi-platform context. MACBenAbim is available from the authors for non-commercial purposes.

  18. Mesangial cell biology

    Energy Technology Data Exchange (ETDEWEB)

    Abboud, Hanna E., E-mail: Abboud@uthscsa.edu

    2012-05-15

    Mesangial cells originate from the metanephric mesenchyme and maintain structural integrity of the glomerular microvascular bed and mesangial matrix homeostasis. In response to metabolic, immunologic or hemodynamic injury, these cells undergo apoptosis or acquire an activated phenotype and undergo hypertrophy, proliferation with excessive production of matrix proteins, growth factors, chemokines and cytokines. These soluble factors exert autocrine and paracrine effects on the cells or on other glomerular cells, respectively. MCs are primary targets of immune-mediated glomerular diseases such as IGA nephropathy or metabolic diseases such as diabetes. MCs may also respond to injury that primarily involves podocytes and endothelial cells or to structural and genetic abnormalities of the glomerular basement membrane. Signal transduction and oxidant stress pathways are activated in MCs and likely represent integrated input from multiple mediators. Such responses are convenient targets for therapeutic intervention. Studies in cultured MCs should be supplemented with in vivo studies as well as examination of freshly isolated cells from normal and diseases glomeruli. In addition to ex vivo morphologic studies in kidney cortex, cells should be studied in their natural environment, isolated glomeruli or even tissue slices. Identification of a specific marker of MCs should help genetic manipulation as well as selective therapeutic targeting of these cells. Identification of biological responses of MCs that are not mediated by the renin–angiotensin system should help development of novel and effective therapeutic strategies to treat diseases characterized by MC pathology.

  19. Mesangial cell biology

    International Nuclear Information System (INIS)

    Abboud, Hanna E.

    2012-01-01

    Mesangial cells originate from the metanephric mesenchyme and maintain structural integrity of the glomerular microvascular bed and mesangial matrix homeostasis. In response to metabolic, immunologic or hemodynamic injury, these cells undergo apoptosis or acquire an activated phenotype and undergo hypertrophy, proliferation with excessive production of matrix proteins, growth factors, chemokines and cytokines. These soluble factors exert autocrine and paracrine effects on the cells or on other glomerular cells, respectively. MCs are primary targets of immune-mediated glomerular diseases such as IGA nephropathy or metabolic diseases such as diabetes. MCs may also respond to injury that primarily involves podocytes and endothelial cells or to structural and genetic abnormalities of the glomerular basement membrane. Signal transduction and oxidant stress pathways are activated in MCs and likely represent integrated input from multiple mediators. Such responses are convenient targets for therapeutic intervention. Studies in cultured MCs should be supplemented with in vivo studies as well as examination of freshly isolated cells from normal and diseases glomeruli. In addition to ex vivo morphologic studies in kidney cortex, cells should be studied in their natural environment, isolated glomeruli or even tissue slices. Identification of a specific marker of MCs should help genetic manipulation as well as selective therapeutic targeting of these cells. Identification of biological responses of MCs that are not mediated by the renin–angiotensin system should help development of novel and effective therapeutic strategies to treat diseases characterized by MC pathology.

  20. 7th World Congress on Nature and Biologically Inspired Computing

    CERN Document Server

    Engelbrecht, Andries; Abraham, Ajith; Plessis, Mathys; Snášel, Václav; Muda, Azah

    2016-01-01

    World Congress on Nature and Biologically Inspired Computing (NaBIC) is organized to discuss the state-of-the-art as well as to address various issues with respect to Nurturing Intelligent Computing Towards Advancement of Machine Intelligence. This Volume contains the papers presented in the Seventh World Congress (NaBIC’15) held in Pietermaritzburg, South Africa during December 01-03, 2015. The 39 papers presented in this Volume were carefully reviewed and selected. The Volume would be a valuable reference to researchers, students and practitioners in the computational intelligence field.

  1. Quantitative stem cell biology: the threat and the glory.

    Science.gov (United States)

    Pollard, Steven M

    2016-11-15

    Major technological innovations over the past decade have transformed our ability to extract quantitative data from biological systems at an unprecedented scale and resolution. These quantitative methods and associated large datasets should lead to an exciting new phase of discovery across many areas of biology. However, there is a clear threat: will we drown in these rivers of data? On 18th July 2016, stem cell biologists gathered in Cambridge for the 5th annual Cambridge Stem Cell Symposium to discuss 'Quantitative stem cell biology: from molecules to models'. This Meeting Review provides a summary of the data presented by each speaker, with a focus on quantitative techniques and the new biological insights that are emerging. © 2016. Published by The Company of Biologists Ltd.

  2. Inter-level relations in computer science, biology, and psychology

    NARCIS (Netherlands)

    Boogerd, Fred; Bruggeman, Frank; Jonker, Catholijn; Looren de Jong, Huib; Tamminga, Allard; Treur, Jan; Westerhoff, Hans; Wijngaards, Wouter

    2002-01-01

    Investigations into inter-level relations in computer science, biology and psychology call for an *empirical* turn in the philosophy of mind. Rather than concentrate on *a priori* discussions of inter-level relations between “completed” sciences, a case is made for the actual study of the way

  3. Inter-level relations in computer science, biology, and psychology

    NARCIS (Netherlands)

    Boogerd, F.; Bruggeman, F.; Jonker, C.M.; Looren de Jong, H.; Tamminga, A.; Treur, J.; Westerhoff, H.V.; Wijngaards, W.C.A.

    2002-01-01

    Investigations into inter-level relations in computer science, biology and psychology call for an empirical turn in the philosophy of mind. Rather than concentrate on a priori discussions of inter-level relations between 'completed' sciences, a case is made for the actual study of the way

  4. Inter-level relations in computer science, biology and psychology

    NARCIS (Netherlands)

    Boogerd, F.C.; Bruggeman, F.J.; Jonker, C.M.; Looren De Jong, H.; Tamminga, A.M.; Treur, J.; Westerhoff, H.V.; Wijngaards, W.C.A.

    2002-01-01

    Investigations into inter-level relations in computer science, biology and psychology call for an empirical turn in the philosophy of mind. Rather than concentrate on a priori discussions of inter-level relations between "completed" sciences, a case is made for the actual study of the way

  5. Application of computational systems biology to explore environmental toxicity hazards

    DEFF Research Database (Denmark)

    Audouze, Karine Marie Laure; Grandjean, Philippe

    2011-01-01

    Background: Computer-based modeling is part of a new approach to predictive toxicology.Objectives: We investigated the usefulness of an integrated computational systems biology approach in a case study involving the isomers and metabolites of the pesticide dichlorodiphenyltrichloroethane (DDT......) to ascertain their possible links to relevant adverse effects.Methods: We extracted chemical-protein association networks for each DDT isomer and its metabolites using ChemProt, a disease chemical biology database that includes both binding and gene expression data, and we explored protein-protein interactions...... using a human interactome network. To identify associated dysfunctions and diseases, we integrated protein-disease annotations into the protein complexes using the Online Mendelian Inheritance in Man database and the Comparative Toxicogenomics Database.Results: We found 175 human proteins linked to p,p´-DDT...

  6. A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES.

    Science.gov (United States)

    Somogyi, Endre; Glazier, James A

    2017-04-01

    Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment.

  7. Computing chemical organizations in biological networks.

    Science.gov (United States)

    Centler, Florian; Kaleta, Christoph; di Fenizio, Pietro Speroni; Dittrich, Peter

    2008-07-15

    Novel techniques are required to analyze computational models of intracellular processes as they increase steadily in size and complexity. The theory of chemical organizations has recently been introduced as such a technique that links the topology of biochemical reaction network models to their dynamical repertoire. The network is decomposed into algebraically closed and self-maintaining subnetworks called organizations. They form a hierarchy representing all feasible system states including all steady states. We present three algorithms to compute the hierarchy of organizations for network models provided in SBML format. Two of them compute the complete organization hierarchy, while the third one uses heuristics to obtain a subset of all organizations for large models. While the constructive approach computes the hierarchy starting from the smallest organization in a bottom-up fashion, the flux-based approach employs self-maintaining flux distributions to determine organizations. A runtime comparison on 16 different network models of natural systems showed that none of the two exhaustive algorithms is superior in all cases. Studying a 'genome-scale' network model with 762 species and 1193 reactions, we demonstrate how the organization hierarchy helps to uncover the model structure and allows to evaluate the model's quality, for example by detecting components and subsystems of the model whose maintenance is not explained by the model. All data and a Java implementation that plugs into the Systems Biology Workbench is available from http://www.minet.uni-jena.de/csb/prj/ot/tools.

  8. Analog synthetic biology.

    Science.gov (United States)

    Sarpeshkar, R

    2014-03-28

    We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic and hybrid analog-digital computational approaches; otherwise, even relatively simple synthetic computations in cells such as addition will exceed energy and molecular-count budgets. We present schematics for efficiently representing analog DNA-protein computation in cells. Analog electronic flow in subthreshold transistors and analog molecular flux in chemical reactions obey Boltzmann exponential laws of thermodynamics and are described by astoundingly similar logarithmic electrochemical potentials. Therefore, cytomorphic circuits can help to map circuit designs between electronic and biochemical domains. We review recent work that uses positive-feedback linearization circuits to architect wide-dynamic-range logarithmic analog computation in Escherichia coli using three transcription factors, nearly two orders of magnitude more efficient in parts than prior digital implementations.

  9. Where mathematics, computer science, linguistics and biology meet essays in honour of Gheorghe Păun

    CERN Document Server

    Mitrana, Victor

    2001-01-01

    In the last years, it was observed an increasing interest of computer scientists in the structure of biological molecules and the way how they can be manipulated in vitro in order to define theoretical models of computation based on genetic engineering tools. Along the same lines, a parallel interest is growing regarding the process of evolution of living organisms. Much of the current data for genomes are expressed in the form of maps which are now becoming available and permit the study of the evolution of organisms at the scale of genome for the first time. On the other hand, there is an active trend nowadays throughout the field of computational biology toward abstracted, hierarchical views of biological sequences, which is very much in the spirit of computational linguistics. In the last decades, results and methods in the field of formal language theory that might be applied to the description of biological sequences were pointed out.

  10. Noninvasive Assessment of Cell Fate and Biology in Transplanted Mesenchymal Stem Cells.

    Science.gov (United States)

    Franchi, Federico; Rodriguez-Porcel, Martin

    2017-01-01

    Recently, molecular imaging has become a conditio sine qua non for cell-based regenerative medicine. Developments in molecular imaging techniques, such as reporter gene technology, have increasingly enabled the noninvasive assessment of the fate and biology of cells after cardiovascular applications. In this context, bioluminescence imaging is the most commonly used imaging modality in small animal models of preclinical studies. Here, we present a detailed protocol of a reporter gene imaging approach for monitoring the viability and biology of Mesenchymal Stem Cells transplanted in a mouse model of myocardial ischemia reperfusion injury.

  11. Identifying niche-mediated regulatory factors of stem cell phenotypic state: a systems biology approach.

    Science.gov (United States)

    Ravichandran, Srikanth; Del Sol, Antonio

    2017-02-01

    Understanding how the cellular niche controls the stem cell phenotype is often hampered due to the complexity of variegated niche composition, its dynamics, and nonlinear stem cell-niche interactions. Here, we propose a systems biology view that considers stem cell-niche interactions as a many-body problem amenable to simplification by the concept of mean field approximation. This enables approximation of the niche effect on stem cells as a constant field that induces sustained activation/inhibition of specific stem cell signaling pathways in all stem cells within heterogeneous populations exhibiting the same phenotype (niche determinants). This view offers a new basis for the development of single cell-based computational approaches for identifying niche determinants, which has potential applications in regenerative medicine and tissue engineering. © 2017 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

  12. Biology Students Building Computer Simulations Using StarLogo TNG

    Science.gov (United States)

    Smith, V. Anne; Duncan, Ishbel

    2011-01-01

    Confidence is an important issue for biology students in handling computational concepts. This paper describes a practical in which honours-level bioscience students simulate complex animal behaviour using StarLogo TNG, a freely-available graphical programming environment. The practical consists of two sessions, the first of which guides students…

  13. The cell biology of T-dependent B cell activation

    DEFF Research Database (Denmark)

    Owens, T; Zeine, R

    1989-01-01

    The requirement that CD4+ helper T cells recognize antigen in association with class II Major Histocompatibility Complex (MHC) encoded molecules constrains T cells to activation through intercellular interaction. The cell biology of the interactions between CD4+ T cells and antigen-presenting cells...... includes multipoint intermolecular interactions that probably involve aggregation of both polymorphic and monomorphic T cell surface molecules. Such aggregations have been shown in vitro to markedly enhance and, in some cases, induce T cell activation. The production of T-derived lymphokines that have been...... implicated in B cell activation is dependent on the T cell receptor for antigen and its associated CD3 signalling complex. T-dependent help for B cell activation is therefore similarly MHC-restricted and involves T-B intercellular interaction. Recent reports that describe antigen-independent B cell...

  14. Community-driven computational biology with Debian Linux.

    Science.gov (United States)

    Möller, Steffen; Krabbenhöft, Hajo Nils; Tille, Andreas; Paleino, David; Williams, Alan; Wolstencroft, Katy; Goble, Carole; Holland, Richard; Belhachemi, Dominique; Plessy, Charles

    2010-12-21

    The Open Source movement and its technologies are popular in the bioinformatics community because they provide freely available tools and resources for research. In order to feed the steady demand for updates on software and associated data, a service infrastructure is required for sharing and providing these tools to heterogeneous computing environments. The Debian Med initiative provides ready and coherent software packages for medical informatics and bioinformatics. These packages can be used together in Taverna workflows via the UseCase plugin to manage execution on local or remote machines. If such packages are available in cloud computing environments, the underlying hardware and the analysis pipelines can be shared along with the software. Debian Med closes the gap between developers and users. It provides a simple method for offering new releases of software and data resources, thus provisioning a local infrastructure for computational biology. For geographically distributed teams it can ensure they are working on the same versions of tools, in the same conditions. This contributes to the world-wide networking of researchers.

  15. A Computational Framework for Bioimaging Simulation

    Science.gov (United States)

    Watabe, Masaki; Arjunan, Satya N. V.; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi

    2015-01-01

    Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units. PMID:26147508

  16. A Computational Framework for Bioimaging Simulation.

    Science.gov (United States)

    Watabe, Masaki; Arjunan, Satya N V; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi

    2015-01-01

    Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units.

  17. A Computational Framework for Bioimaging Simulation.

    Directory of Open Access Journals (Sweden)

    Masaki Watabe

    Full Text Available Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units.

  18. Automatic detection of biological cells

    International Nuclear Information System (INIS)

    Alves Da Costa, Caiuby

    1983-01-01

    The present research work has dealt with the analysis of biological cell images in general, and more specially with the cervical cells. This work was carried out in order to develop an automaton leading to a better prevention of cancer through automated mass screening. The device has been implemented on Motorola 68.000 microprocessor system. The automaton carries out cell nucleus analysis in several steps. The main steps are: - First: the automaton focuses on an individual cell nucleus among the smear's cell (about 10.000), - Second: it process each nucleus image. The digital processing yields geometrical of the nucleus (area and perimeter) for each cell. These data are stored in a local memory for further discriminant analysis by a microcomputer. In this way smears are classed in two groups: hale smears and uncertain smears. The automaton uses a wired logic for image acquisition and its software algorithms provide image reconstruction. The reconstruction algorithms are general purpose. Tests have proved that they can reconstruct any two dimensional images independently of its geometrical form. Moreover they can make the reconstruction of any image among the several images present in observation field. The processing times registered during the tests (for different cases) were situated, all of them, below three minutes for 10,000 images (each of them formed by an average of 450 pixels). The interest of the method is generality and speed. The only restriction is the primary device sensor (CCD linear array) length. Thus the automaton application can be extended beyond the biological image field. (author) [fr

  19. A Diagnostic Assessment for Introductory Molecular and Cell Biology

    Science.gov (United States)

    Shi, Jia; Wood, William B.; Martin, Jennifer M.; Guild, Nancy A.; Vicens, Quentin; Knight, Jennifer K.

    2010-01-01

    We have developed and validated a tool for assessing understanding of a selection of fundamental concepts and basic knowledge in undergraduate introductory molecular and cell biology, focusing on areas in which students often have misconceptions. This multiple-choice Introductory Molecular and Cell Biology Assessment (IMCA) instrument is designed…

  20. Glial cell biology in the Great Lakes region.

    Science.gov (United States)

    Feinstein, Douglas L; Skoff, Robert P

    2016-03-31

    We report on the tenth bi-annual Great Lakes Glial meeting, held in Traverse City, Michigan, USA, September 27-29 2015. The GLG meeting is a small conference that focuses on current research in glial cell biology. The array of functions that glial cells (astrocytes, microglia, oligodendrocytes, Schwann cells) play in health and disease is constantly increasing. Despite this diversity, GLG meetings bring together scientists with common interests, leading to a better understanding of these cells. This year's meeting included two keynote speakers who presented talks on the regulation of CNS myelination and the consequences of stress on Schwann cell biology. Twenty-two other talks were presented along with two poster sessions. Sessions covered recent findings in the areas of microglial and astrocyte activation; age-dependent changes to glial cells, Schwann cell development and pathology, and the role of stem cells in glioma and neural regeneration.

  1. The synergistic use of computation, chemistry and biology to discover novel peptide-based drugs: the time is right.

    Science.gov (United States)

    Audie, J; Boyd, C

    2010-01-01

    The case for peptide-based drugs is compelling. Due to their chemical, physical and conformational diversity, and relatively unproblematic toxicity and immunogenicity, peptides represent excellent starting material for drug discovery. Nature has solved many physiological and pharmacological problems through the use of peptides, polypeptides and proteins. If nature could solve such a diversity of challenging biological problems through the use of peptides, it seems reasonable to infer that human ingenuity will prove even more successful. And this, indeed, appears to be the case, as a number of scientific and methodological advances are making peptides and peptide-based compounds ever more promising pharmacological agents. Chief among these advances are powerful chemical and biological screening technologies for lead identification and optimization, methods for enhancing peptide in vivo stability, bioavailability and cell-permeability, and new delivery technologies. Other advances include the development and experimental validation of robust computational methods for peptide lead identification and optimization. Finally, scientific analysis, biology and chemistry indicate the prospect of designing relatively small peptides to therapeutically modulate so-called 'undruggable' protein-protein interactions. Taken together a clear picture is emerging: through the synergistic use of the scientific imagination and the computational, chemical and biological methods that are currently available, effective peptide therapeutics for novel targets can be designed that surpass even the proven peptidic designs of nature.

  2. Molecular biology of mycoplasmas: from the minimum cell concept to the artificial cell.

    Science.gov (United States)

    Cordova, Caio M M; Hoeltgebaum, Daniela L; Machado, Laís D P N; Santos, Larissa Dos

    2016-01-01

    Mycoplasmas are a large group of bacteria, sorted into different genera in the Mollicutes class, whose main characteristic in common, besides the small genome, is the absence of cell wall. They are considered cellular and molecular biology study models. We present an updated review of the molecular biology of these model microorganisms and the development of replicative vectors for the transformation of mycoplasmas. Synthetic biology studies inspired by these pioneering works became possible and won the attention of the mainstream media. For the first time, an artificial genome was synthesized (a minimal genome produced from consensus sequences obtained from mycoplasmas). For the first time, a functional artificial cell has been constructed by introducing a genome completely synthesized within a cell envelope of a mycoplasma obtained by transformation techniques. Therefore, this article offers an updated insight to the state of the art of these peculiar organisms' molecular biology.

  3. METABOLIC MODELLING IN THE DEVELOPMENT OF CELL FACTORIES BY SYNTHETIC BIOLOGY

    Directory of Open Access Journals (Sweden)

    Paula Jouhten

    2012-10-01

    Full Text Available Cell factories are commonly microbial organisms utilized for bioconversion of renewable resources to bulk or high value chemicals. Introduction of novel production pathways in chassis strains is the core of the development of cell factories by synthetic biology. Synthetic biology aims to create novel biological functions and systems not found in nature by combining biology with engineering. The workflow of the development of novel cell factories with synthetic biology is ideally linear which will be attainable with the quantitative engineering approach, high-quality predictive models, and libraries of well-characterized parts. Different types of metabolic models, mathematical representations of metabolism and its components, enzymes and metabolites, are useful in particular phases of the synthetic biology workflow. In this minireview, the role of metabolic modelling in synthetic biology will be discussed with a review of current status of compatible methods and models for the in silico design and quantitative evaluation of a cell factory.

  4. Integrative systems and synthetic biology of cell-matrix adhesion sites.

    Science.gov (United States)

    Zamir, Eli

    2016-09-02

    The complexity of cell-matrix adhesion convolves its roles in the development and functioning of multicellular organisms and their evolutionary tinkering. Cell-matrix adhesion is mediated by sites along the plasma membrane that anchor the actin cytoskeleton to the matrix via a large number of proteins, collectively called the integrin adhesome. Fundamental challenges for understanding how cell-matrix adhesion sites assemble and function arise from their multi-functionality, rapid dynamics, large number of components and molecular diversity. Systems biology faces these challenges in its strive to understand how the integrin adhesome gives rise to functional adhesion sites. Synthetic biology enables engineering intracellular modules and circuits with properties of interest. In this review I discuss some of the fundamental questions in systems biology of cell-matrix adhesion and how synthetic biology can help addressing them.

  5. The transhumanism of Ray Kurzweil. Is biological ontology reducible to computation?

    Directory of Open Access Journals (Sweden)

    Javier Monserrat

    2016-02-01

    Full Text Available Computer programs, primarily engineering machine vision and programming of somatic sensors, have already allowed, and they will do it more perfectly in the future, to build high perfection androids or cyborgs. They will collaborate with man and open new moral reflections to respect the ontological dignity in the new humanoid machines. In addition, both men and new androids will be in connection with huge external computer networks that will grow up to almost incredible levels the efficiency in the domain of body and nature. However, our current scientific knowledge, on the one hand, about hardware and software that will support both the humanoid machines and external computer networks, made with existing engineering (and also the foreseeable medium and even long term engineering and, on the other hand, our scientific knowledge about animal and human behavior from neural-biological structures that produce a psychic system, allow us to establish that there is no scientific basis to talk about an ontological identity between the computational machines and man. Accordingly, different ontologies (computational machines and biological entities will produce various different functional systems. There may be simulation, but never ontological identity. These ideas are essential to assess the transhumanism of Ray Kurzweil.

  6. Computer control of shielded cell operations

    International Nuclear Information System (INIS)

    Jeffords, W.R. III.

    1987-01-01

    This paper describes in detail a computer system to remotely control shielded cell operations. System hardware, software, and design criteria are discussed. We have designed a computer-controlled buret that provides a tenfold improvement over the buret currently in service. A computer also automatically controls cell analyses, calibrations, and maintenance. This system improves conditions for the operators by providing a safer, more efficient working environment and is expandable for future growth and development

  7. The changing world of modern cell biology.

    Science.gov (United States)

    Misteli, Tom

    2009-01-12

    Change is always ambiguous. There is the enticing prospect of novelty and better times ahead, but at the same time the concern of losing the good of the past. It is with these sentiments that I take over as the Editor-in-Chief from Ira Mellman who for a decade has cleverly and effectively lead the JCB. During this time he directed and oversaw an extensive modernization of the journal and guided it through dramatic changes in the publishing world. Ira lead the journal with unyielding dedication and enthusiasm and we in the cell biology community must thank him profoundly for his service. It is his work, together with the invaluable contribution of the best editorial board and the most dedicated professional editorial staff in the scientific publishing business, that allows me to now take over the stewardship of the JCB with a tremendous sense of excitement and determination to continue and expand the JCB's role as the leading journal in the cell biology community and as a trendsetter in the rapidly changing world of modern cell biology.

  8. A framework to establish credibility of computational models in biology.

    Science.gov (United States)

    Patterson, Eann A; Whelan, Maurice P

    2017-10-01

    Computational models in biology and biomedical science are often constructed to aid people's understanding of phenomena or to inform decisions with socioeconomic consequences. Model credibility is the willingness of people to trust a model's predictions and is often difficult to establish for computational biology models. A 3 × 3 matrix has been proposed to allow such models to be categorised with respect to their testability and epistemic foundation in order to guide the selection of an appropriate process of validation to supply evidence to establish credibility. Three approaches to validation are identified that can be deployed depending on whether a model is deemed untestable, testable or lies somewhere in between. In the latter two cases, the validation process involves the quantification of uncertainty which is a key output. The issues arising due to the complexity and inherent variability of biological systems are discussed and the creation of 'digital twins' proposed as a means to alleviate the issues and provide a more robust, transparent and traceable route to model credibility and acceptance. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  9. Investigating the role of retinal Müller cells with approaches in genetics and cell biology.

    Science.gov (United States)

    Fu, Suhua; Zhu, Meili; Ash, John D; Wang, Yunchang; Le, Yun-Zheng

    2014-01-01

    Müller cells are major macroglia and play many essential roles as a supporting cell in the retina. As Müller cells only constitute a small portion of retinal cells, investigating the role of Müller glia in retinal biology and diseases is particularly challenging. To overcome this problem, we first generated a Cre/lox-based conditional gene targeting system that permits the genetic manipulation and functional dissection of gene of interests in Müller cells. To investigate diabetes-induced alteration of Müller cells, we recently adopted methods to analyze Müller cells survival/death in vitro and in vivo. We also used normal and genetically altered primary cell cultures to reveal the mechanistic insights for Müller cells in biological and disease processes. In this article, we will discuss the applications and limitations of these methodologies, which may be useful for research in retinal Müller cell biology and pathophysiology.

  10. Exploiting graphics processing units for computational biology and bioinformatics.

    Science.gov (United States)

    Payne, Joshua L; Sinnott-Armstrong, Nicholas A; Moore, Jason H

    2010-09-01

    Advances in the video gaming industry have led to the production of low-cost, high-performance graphics processing units (GPUs) that possess more memory bandwidth and computational capability than central processing units (CPUs), the standard workhorses of scientific computing. With the recent release of generalpurpose GPUs and NVIDIA's GPU programming language, CUDA, graphics engines are being adopted widely in scientific computing applications, particularly in the fields of computational biology and bioinformatics. The goal of this article is to concisely present an introduction to GPU hardware and programming, aimed at the computational biologist or bioinformaticist. To this end, we discuss the primary differences between GPU and CPU architecture, introduce the basics of the CUDA programming language, and discuss important CUDA programming practices, such as the proper use of coalesced reads, data types, and memory hierarchies. We highlight each of these topics in the context of computing the all-pairs distance between instances in a dataset, a common procedure in numerous disciplines of scientific computing. We conclude with a runtime analysis of the GPU and CPU implementations of the all-pairs distance calculation. We show our final GPU implementation to outperform the CPU implementation by a factor of 1700.

  11. Evolutionary cell biology: functional insight from "endless forms most beautiful".

    Science.gov (United States)

    Richardson, Elisabeth; Zerr, Kelly; Tsaousis, Anastasios; Dorrell, Richard G; Dacks, Joel B

    2015-12-15

    In animal and fungal model organisms, the complexities of cell biology have been analyzed in exquisite detail and much is known about how these organisms function at the cellular level. However, the model organisms cell biologists generally use include only a tiny fraction of the true diversity of eukaryotic cellular forms. The divergent cellular processes observed in these more distant lineages are still largely unknown in the general scientific community. Despite the relative obscurity of these organisms, comparative studies of them across eukaryotic diversity have had profound implications for our understanding of fundamental cell biology in all species and have revealed the evolution and origins of previously observed cellular processes. In this Perspective, we will discuss the complexity of cell biology found across the eukaryotic tree, and three specific examples of where studies of divergent cell biology have altered our understanding of key functional aspects of mitochondria, plastids, and membrane trafficking. © 2015 Richardson et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  12. Eduard Strasburger (1844-1912): founder of modern plant cell biology.

    Science.gov (United States)

    Volkmann, Dieter; Baluška, František; Menzel, Diedrik

    2012-10-01

    Eduard Strasburger, director of the Botany Institute and the Botanical Garden at the University of Bonn from 1881 to 1912, was one of the most admirable scientists in the field of plant biology, not just as the founder of modern plant cell biology but in addition as an excellent teacher who strongly believed in "education through science." He contributed to plant cell biology by discovering the discrete stages of karyokinesis and cytokinesis in algae and higher plants, describing cytoplasmic streaming in different systems, and reporting on the growth of the pollen tube into the embryo sac and guidance of the tube by synergides. Strasburger raised many problems which are hot spots in recent plant cell biology, e.g., structure and function of the plasmodesmata in relation to phloem loading (Strasburger cells) and signaling, mechanisms of cell plate formation, vesicle trafficking as a basis for most important developmental processes, and signaling related to fertilization.

  13. A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells.

    Science.gov (United States)

    Trevino, Victor; Cassese, Alberto; Nagy, Zsuzsanna; Zhuang, Xiaodong; Herbert, John; Antczak, Philipp; Clarke, Kim; Davies, Nicholas; Rahman, Ayesha; Campbell, Moray J; Guindani, Michele; Bicknell, Roy; Vannucci, Marina; Falciani, Francesco

    2016-04-01

    The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell communication networks

  14. A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells.

    Directory of Open Access Journals (Sweden)

    Victor Trevino

    2016-04-01

    Full Text Available The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell

  15. Scalable Computational Methods for the Analysis of High-Throughput Biological Data

    Energy Technology Data Exchange (ETDEWEB)

    Langston, Michael A. [Univ. of Tennessee, Knoxville, TN (United States)

    2012-09-06

    This primary focus of this research project is elucidating genetic regulatory mechanisms that control an organism's responses to low-dose ionizing radiation. Although low doses (at most ten centigrays) are not lethal to humans, they elicit a highly complex physiological response, with the ultimate outcome in terms of risk to human health unknown. The tools of molecular biology and computational science will be harnessed to study coordinated changes in gene expression that orchestrate the mechanisms a cell uses to manage the radiation stimulus. High performance implementations of novel algorithms that exploit the principles of fixed-parameter tractability will be used to extract gene sets suggestive of co-regulation. Genomic mining will be performed to scrutinize, winnow and highlight the most promising gene sets for more detailed investigation. The overall goal is to increase our understanding of the health risks associated with exposures to low levels of radiation.

  16. Computational Systems Chemical Biology

    OpenAIRE

    Oprea, Tudor I.; May, Elebeoba E.; Leitão, Andrei; Tropsha, Alexander

    2011-01-01

    There is a critical need for improving the level of chemistry awareness in systems biology. The data and information related to modulation of genes and proteins by small molecules continue to accumulate at the same time as simulation tools in systems biology and whole body physiologically-based pharmacokinetics (PBPK) continue to evolve. We called this emerging area at the interface between chemical biology and systems biology systems chemical biology, SCB (Oprea et al., 2007).

  17. Systems biology perspectives on minimal and simpler cells.

    Science.gov (United States)

    Xavier, Joana C; Patil, Kiran Raosaheb; Rocha, Isabel

    2014-09-01

    The concept of the minimal cell has fascinated scientists for a long time, from both fundamental and applied points of view. This broad concept encompasses extreme reductions of genomes, the last universal common ancestor (LUCA), the creation of semiartificial cells, and the design of protocells and chassis cells. Here we review these different areas of research and identify common and complementary aspects of each one. We focus on systems biology, a discipline that is greatly facilitating the classical top-down and bottom-up approaches toward minimal cells. In addition, we also review the so-called middle-out approach and its contributions to the field with mathematical and computational models. Owing to the advances in genomics technologies, much of the work in this area has been centered on minimal genomes, or rather minimal gene sets, required to sustain life. Nevertheless, a fundamental expansion has been taking place in the last few years wherein the minimal gene set is viewed as a backbone of a more complex system. Complementing genomics, progress is being made in understanding the system-wide properties at the levels of the transcriptome, proteome, and metabolome. Network modeling approaches are enabling the integration of these different omics data sets toward an understanding of the complex molecular pathways connecting genotype to phenotype. We review key concepts central to the mapping and modeling of this complexity, which is at the heart of research on minimal cells. Finally, we discuss the distinction between minimizing the number of cellular components and minimizing cellular complexity, toward an improved understanding and utilization of minimal and simpler cells. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

  18. Systems Biology Perspectives on Minimal and Simpler Cells

    Science.gov (United States)

    Xavier, Joana C.; Patil, Kiran Raosaheb

    2014-01-01

    SUMMARY The concept of the minimal cell has fascinated scientists for a long time, from both fundamental and applied points of view. This broad concept encompasses extreme reductions of genomes, the last universal common ancestor (LUCA), the creation of semiartificial cells, and the design of protocells and chassis cells. Here we review these different areas of research and identify common and complementary aspects of each one. We focus on systems biology, a discipline that is greatly facilitating the classical top-down and bottom-up approaches toward minimal cells. In addition, we also review the so-called middle-out approach and its contributions to the field with mathematical and computational models. Owing to the advances in genomics technologies, much of the work in this area has been centered on minimal genomes, or rather minimal gene sets, required to sustain life. Nevertheless, a fundamental expansion has been taking place in the last few years wherein the minimal gene set is viewed as a backbone of a more complex system. Complementing genomics, progress is being made in understanding the system-wide properties at the levels of the transcriptome, proteome, and metabolome. Network modeling approaches are enabling the integration of these different omics data sets toward an understanding of the complex molecular pathways connecting genotype to phenotype. We review key concepts central to the mapping and modeling of this complexity, which is at the heart of research on minimal cells. Finally, we discuss the distinction between minimizing the number of cellular components and minimizing cellular complexity, toward an improved understanding and utilization of minimal and simpler cells. PMID:25184563

  19. Multiobjective optimization in bioinformatics and computational biology.

    Science.gov (United States)

    Handl, Julia; Kell, Douglas B; Knowles, Joshua

    2007-01-01

    This paper reviews the application of multiobjective optimization in the fields of bioinformatics and computational biology. A survey of existing work, organized by application area, forms the main body of the review, following an introduction to the key concepts in multiobjective optimization. An original contribution of the review is the identification of five distinct "contexts," giving rise to multiple objectives: These are used to explain the reasons behind the use of multiobjective optimization in each application area and also to point the way to potential future uses of the technique.

  20. Impact of implementation choices on quantitative predictions of cell-based computational models

    Science.gov (United States)

    Kursawe, Jochen; Baker, Ruth E.; Fletcher, Alexander G.

    2017-09-01

    'Cell-based' models provide a powerful computational tool for studying the mechanisms underlying the growth and dynamics of biological tissues in health and disease. An increasing amount of quantitative data with cellular resolution has paved the way for the quantitative parameterisation and validation of such models. However, the numerical implementation of cell-based models remains challenging, and little work has been done to understand to what extent implementation choices may influence model predictions. Here, we consider the numerical implementation of a popular class of cell-based models called vertex models, which are often used to study epithelial tissues. In two-dimensional vertex models, a tissue is approximated as a tessellation of polygons and the vertices of these polygons move due to mechanical forces originating from the cells. Such models have been used extensively to study the mechanical regulation of tissue topology in the literature. Here, we analyse how the model predictions may be affected by numerical parameters, such as the size of the time step, and non-physical model parameters, such as length thresholds for cell rearrangement. We find that vertex positions and summary statistics are sensitive to several of these implementation parameters. For example, the predicted tissue size decreases with decreasing cell cycle durations, and cell rearrangement may be suppressed by large time steps. These findings are counter-intuitive and illustrate that model predictions need to be thoroughly analysed and implementation details carefully considered when applying cell-based computational models in a quantitative setting.

  1. Computational biology approaches to plant metabolism and photosynthesis: applications for corals in times of climate change and environmental stress.

    Science.gov (United States)

    Crabbe, M James C

    2010-08-01

    Knowledge of factors that are important in reef resilience helps us to understand how reef ecosystems react following major anthropogenic and environmental disturbances. The symbiotic relationship between the photosynthetic zooxanthellae algal cells and corals is that the zooxanthellae provide the coral with carbon, while the coral provides protection and access to enough light for the zooxanthellae to photosynthesise. This article reviews some recent advances in computational biology relevant to photosynthetic organisms, including Beyesian approaches to kinetics, computational methods for flux balances in metabolic processes, and determination of clades of zooxanthallae. Application of these systems will be important in the conservation of coral reefs in times of climate change and environmental stress.

  2. Probing the biology of cell boundary conditions through confinement of Xenopus cell-free cytoplasmic extracts.

    Science.gov (United States)

    Bermudez, Jessica G; Chen, Hui; Einstein, Lily C; Good, Matthew C

    2017-01-01

    Cell-free cytoplasmic extracts prepared from Xenopus eggs and embryos have for decades provided a biochemical system with which to interrogate complex cell biological processes in vitro. Recently, the application of microfabrication and microfluidic strategies in biology has narrowed the gap between in vitro and in vivo studies by enabling formation of cell-size compartments containing functional cytoplasm. These approaches provide numerous advantages over traditional biochemical experiments performed in a test tube. Most notably, the cell-free cytoplasm is confined using a two- or three-dimensional boundary, which mimics the natural configuration of a cell. This strategy enables characterization of the spatial organization of a cell, and the role that boundaries play in regulating intracellular assembly and function. In this review, we describe the marriage of Xenopus cell-free cytoplasm and confinement technologies to generate synthetic cell-like systems, the recent biological insights they have enabled, and the promise they hold for future scientific discovery. © 2017 Wiley Periodicals, Inc.

  3. CellNet: Network Biology Applied to Stem Cell Engineering

    Science.gov (United States)

    Cahan, Patrick; Li, Hu; Morris, Samantha A.; da Rocha, Edroaldo Lummertz; Daley, George Q.; Collins, James J.

    2014-01-01

    SUMMARY Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population, and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering. PMID:25126793

  4. CellNet: network biology applied to stem cell engineering.

    Science.gov (United States)

    Cahan, Patrick; Li, Hu; Morris, Samantha A; Lummertz da Rocha, Edroaldo; Daley, George Q; Collins, James J

    2014-08-14

    Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. A muscle stem cell for every muscle: variability of satellite cell biology among different muscle groups

    Science.gov (United States)

    Randolph, Matthew E.; Pavlath, Grace K.

    2015-01-01

    The human body contains approximately 640 individual skeletal muscles. Despite the fact that all of these muscles are composed of striated muscle tissue, the biology of these muscles and their associated muscle stem cell populations are quite diverse. Skeletal muscles are affected differentially by various muscular dystrophies (MDs), such that certain genetic mutations specifically alter muscle function in only a subset of muscles. Additionally, defective muscle stem cells have been implicated in the pathology of some MDs. The biology of muscle stem cells varies depending on the muscles with which they are associated. Here we review the biology of skeletal muscle stem cell populations of eight different muscle groups. Understanding the biological variation of skeletal muscles and their resident stem cells could provide valuable insight into mechanisms underlying the susceptibility of certain muscles to myopathic disease. PMID:26500547

  6. The Emerging Cell Biology of Thyroid Stem Cells

    Science.gov (United States)

    Latif, Rauf; Minsky, Noga C.; Ma, Risheng

    2011-01-01

    Context: Stem cells are undifferentiated cells with the property of self-renewal and give rise to highly specialized cells under appropriate local conditions. The use of stem cells in regenerative medicine holds great promise for the treatment of many diseases, including those of the thyroid gland. Evidence Acquisition: This review focuses on the progress that has been made in thyroid stem cell research including an overview of cellular and molecular events (most of which were drawn from the period 1990–2011) and discusses the remaining problems encountered in their differentiation. Evidence Synthesis: Protocols for the in vitro differentiation of embryonic stem cells, based on normal developmental processes, have generated thyroid-like cells but without full thyrocyte function. However, agents have been identified, including activin A, insulin, and IGF-I, which are able to stimulate the generation of thyroid-like cells in vitro. In addition, thyroid stem/progenitor cells have been identified within the normal thyroid gland and within thyroid cancers. Conclusions: Advances in thyroid stem cell biology are providing not only insight into thyroid development but may offer therapeutic potential in thyroid cancer and future thyroid cell replacement therapy. PMID:21778219

  7. Searching the literature for proteins facilitates the identification of biological processes, if advanced methods of analysis are linked: a case study on microgravity-caused changes in cells.

    Science.gov (United States)

    Bauer, Johann; Bussen, Markus; Wise, Petra; Wehland, Markus; Schneider, Sabine; Grimm, Daniela

    2016-07-01

    More than one hundred reports were published about the characterization of cells from malignant and healthy tissues, as well as of endothelial cells and stem cells exposed to microgravity conditions. We retrieved publications about microgravity related studies on each type of cells, extracted the proteins mentioned therein and analyzed them aiming to identify biological processes affected by microgravity culture conditions. The analysis revealed 66 different biological processes, 19 of them were always detected when papers about the four types of cells were analyzed. Since a response to the removal of gravity is common to the different cell types, some of the 19 biological processes could play a role in cellular adaption to microgravity. Applying computer programs, to extract and analyze proteins and genes mentioned in publications becomes essential for scientists interested to get an overview of the rapidly growing fields of gravitational biology and space medicine.

  8. Scientific Computing Kernels on the Cell Processor

    Energy Technology Data Exchange (ETDEWEB)

    Williams, Samuel W.; Shalf, John; Oliker, Leonid; Kamil, Shoaib; Husbands, Parry; Yelick, Katherine

    2007-04-04

    The slowing pace of commodity microprocessor performance improvements combined with ever-increasing chip power demands has become of utmost concern to computational scientists. As a result, the high performance computing community is examining alternative architectures that address the limitations of modern cache-based designs. In this work, we examine the potential of using the recently-released STI Cell processor as a building block for future high-end computing systems. Our work contains several novel contributions. First, we introduce a performance model for Cell and apply it to several key scientific computing kernels: dense matrix multiply, sparse matrix vector multiply, stencil computations, and 1D/2D FFTs. The difficulty of programming Cell, which requires assembly level intrinsics for the best performance, makes this model useful as an initial step in algorithm design and evaluation. Next, we validate the accuracy of our model by comparing results against published hardware results, as well as our own implementations on a 3.2GHz Cell blade. Additionally, we compare Cell performance to benchmarks run on leading superscalar (AMD Opteron), VLIW (Intel Itanium2), and vector (Cray X1E) architectures. Our work also explores several different mappings of the kernels and demonstrates a simple and effective programming model for Cell's unique architecture. Finally, we propose modest microarchitectural modifications that could significantly increase the efficiency of double-precision calculations. Overall results demonstrate the tremendous potential of the Cell architecture for scientific computations in terms of both raw performance and power efficiency.

  9. Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems.

    Science.gov (United States)

    Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C; Hoeng, Julia

    2015-01-01

    With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com © The Author(s) 2015. Published by Oxford University Press.

  10. S100A4 and its role in metastasis – computational integration of data on biological networks.

    Science.gov (United States)

    Buetti-Dinh, Antoine; Pivkin, Igor V; Friedman, Ran

    2015-08-01

    Characterising signal transduction networks is fundamental to our understanding of biology. However, redundancy and different types of feedback mechanisms make it difficult to understand how variations of the network components contribute to a biological process. In silico modelling of signalling interactions therefore becomes increasingly useful for the development of successful therapeutic approaches. Unfortunately, quantitative information cannot be obtained for all of the proteins or complexes that comprise the network, which limits the usability of computational models. We developed a flexible computational framework for the analysis of biological signalling networks. We demonstrate our approach by studying the mechanism of metastasis promotion by the S100A4 protein, and suggest therapeutic strategies. The advantage of the proposed method is that only limited information (interaction type between species) is required to set up a steady-state network model. This permits a straightforward integration of experimental information where the lack of details are compensated by efficient sampling of the parameter space. We investigated regulatory properties of the S100A4 network and the role of different key components. The results show that S100A4 enhances the activity of matrix metalloproteinases (MMPs), causing higher cell dissociation. Moreover, it leads to an increased stability of the pathological state. Thus, avoiding metastasis in S100A4-expressing tumours requires multiple target inhibition. Moreover, the analysis could explain the previous failure of MMP inhibitors in clinical trials. Finally, our method is applicable to a wide range of biological questions that can be represented as directional networks.

  11. Systems-biology dissection of eukaryotic cell growth

    Directory of Open Access Journals (Sweden)

    Andrews Justen

    2010-05-01

    Full Text Available Abstract A recent article in BMC Biology illustrates the use of a systems-biology approach to integrate data across the transcriptome, proteome and metabolome of budding yeast in order to dissect the relationship between nutrient conditions and cell growth. See research article http://jbiol.com/content/6/2/4 and http://www.biomedcentral.com/1741-7007/8/68

  12. Illuminating Cell Biology

    Science.gov (United States)

    2002-01-01

    NASA's Ames Research Center awarded Ciencia, Inc., a Small Business Innovation Research contract to develop the Cell Fluorescence Analysis System (CFAS) to address the size, mass, and power constraints of using fluorescence spectroscopy in the International Space Station's Life Science Research Facility. The system will play an important role in studying biological specimen's long-term adaptation to microgravity. Commercial applications for the technology include diverse markets such as food safety, in situ environmental monitoring, online process analysis, genomics and DNA chips, and non-invasive diagnostics. Ciencia has already sold the system to the private sector for biosensor applications.

  13. Controllability and observability of Boolean networks arising from biology

    Science.gov (United States)

    Li, Rui; Yang, Meng; Chu, Tianguang

    2015-02-01

    Boolean networks are currently receiving considerable attention as a computational scheme for system level analysis and modeling of biological systems. Studying control-related problems in Boolean networks may reveal new insights into the intrinsic control in complex biological systems and enable us to develop strategies for manipulating biological systems using exogenous inputs. This paper considers controllability and observability of Boolean biological networks. We propose a new approach, which draws from the rich theory of symbolic computation, to solve the problems. Consequently, simple necessary and sufficient conditions for reachability, controllability, and observability are obtained, and algorithmic tests for controllability and observability which are based on the Gröbner basis method are presented. As practical applications, we apply the proposed approach to several different biological systems, namely, the mammalian cell-cycle network, the T-cell activation network, the large granular lymphocyte survival signaling network, and the Drosophila segment polarity network, gaining novel insights into the control and/or monitoring of the specific biological systems.

  14. ADAM: analysis of discrete models of biological systems using computer algebra.

    Science.gov (United States)

    Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

    2011-07-20

    Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web

  15. Secure Encapsulation and Publication of Biological Services in the Cloud Computing Environment

    Science.gov (United States)

    Zhang, Weizhe; Wang, Xuehui; Lu, Bo; Kim, Tai-hoon

    2013-01-01

    Secure encapsulation and publication for bioinformatics software products based on web service are presented, and the basic function of biological information is realized in the cloud computing environment. In the encapsulation phase, the workflow and function of bioinformatics software are conducted, the encapsulation interfaces are designed, and the runtime interaction between users and computers is simulated. In the publication phase, the execution and management mechanisms and principles of the GRAM components are analyzed. The functions such as remote user job submission and job status query are implemented by using the GRAM components. The services of bioinformatics software are published to remote users. Finally the basic prototype system of the biological cloud is achieved. PMID:24078906

  16. Secure Encapsulation and Publication of Biological Services in the Cloud Computing Environment

    Directory of Open Access Journals (Sweden)

    Weizhe Zhang

    2013-01-01

    Full Text Available Secure encapsulation and publication for bioinformatics software products based on web service are presented, and the basic function of biological information is realized in the cloud computing environment. In the encapsulation phase, the workflow and function of bioinformatics software are conducted, the encapsulation interfaces are designed, and the runtime interaction between users and computers is simulated. In the publication phase, the execution and management mechanisms and principles of the GRAM components are analyzed. The functions such as remote user job submission and job status query are implemented by using the GRAM components. The services of bioinformatics software are published to remote users. Finally the basic prototype system of the biological cloud is achieved.

  17. Secure encapsulation and publication of biological services in the cloud computing environment.

    Science.gov (United States)

    Zhang, Weizhe; Wang, Xuehui; Lu, Bo; Kim, Tai-hoon

    2013-01-01

    Secure encapsulation and publication for bioinformatics software products based on web service are presented, and the basic function of biological information is realized in the cloud computing environment. In the encapsulation phase, the workflow and function of bioinformatics software are conducted, the encapsulation interfaces are designed, and the runtime interaction between users and computers is simulated. In the publication phase, the execution and management mechanisms and principles of the GRAM components are analyzed. The functions such as remote user job submission and job status query are implemented by using the GRAM components. The services of bioinformatics software are published to remote users. Finally the basic prototype system of the biological cloud is achieved.

  18. Parallel computing and molecular dynamics of biological membranes

    International Nuclear Information System (INIS)

    La Penna, G.; Letardi, S.; Minicozzi, V.; Morante, S.; Rossi, G.C.; Salina, G.

    1998-01-01

    In this talk I discuss the general question of the portability of molecular dynamics codes for diffusive systems on parallel computers of the APE family. The intrinsic single precision of the today available platforms does not seem to affect the numerical accuracy of the simulations, while the absence of integer addressing from CPU to individual nodes puts strong constraints on possible programming strategies. Liquids can be satisfactorily simulated using the ''systolic'' method. For more complex systems, like the biological ones at which we are ultimately interested in, the ''domain decomposition'' approach is best suited to beat the quadratic growth of the inter-molecular computational time with the number of atoms of the system. The promising perspectives of using this strategy for extensive simulations of lipid bilayers are briefly reviewed. (orig.)

  19. Influence of cell printing on biological characters of chondrocytes.

    Science.gov (United States)

    Qu, Miao; Gao, Xiaoyan; Hou, Yikang; Shen, Congcong; Xu, Yourong; Zhu, Ming; Wang, Hengjian; Xu, Haisong; Chai, Gang; Zhang, Yan

    2015-01-01

    To establish a two-dimensional biological printing technique of chondrocytes and compare the difference of related biological characters between printed chondrocytes and unprinted cells so as to control the cell transfer process and keep cell viability after printing. Primary chondrocytes were obtained from human mature and fetal cartilage tissues and then were regularly sub-cultured to harvest cells at passage 2 (P2), which were adjusted to the single cell suspension at a density of 1×10(6)/mL. The experiment was divided into 2 groups: experimental group P2 chondrocytes were transferred by rapid prototype biological printer (driving voltage value 50 V, interval in x-axis 300 μm, interval in y-axis 1500 μm). Afterwards Live/Dead viability Kit and flow cytometry were respectively adopted to detect cell viability; CCK-8 Kit was adopted to detect cell proliferation viability; immunocytochemistry, immunofluorescence and RT-PCR was employed to identify related markers of chondrocytes; control group steps were the same as the printing group except that cell suspension received no printing. Fluorescence microscopy and flow cytometry analyses showed that there was no significant difference between experimental group and control group in terms of cell viability. After 7-day in vitro culture, control group exhibited higher O.D values than experimental group from 2nd day to 7th day but there was no distinct difference between these two groups (P>0.05). Inverted microscope observation demonstrated that the morphology of these two groups had no significant difference either. Similarly, Immunocytochemistry, immunofluorescence and RT-PCR assays also showed that there was no significant difference in the protein and gene expression of type II collagen and aggrecan between these two groups (P>0.05). Conclusion Cell printing has no distinctly negative effect on cell vitality, proliferation and phenotype of chondrocytes. Biological printing technique may provide a novel approach

  20. Micro-separation toward systems biology.

    Science.gov (United States)

    Liu, Bi-Feng; Xu, Bo; Zhang, Guisen; Du, Wei; Luo, Qingming

    2006-02-17

    Current biology is experiencing transformation in logic or philosophy that forces us to reevaluate the concept of cell, tissue or entire organism as a collection of individual components. Systems biology that aims at understanding biological system at the systems level is an emerging research area, which involves interdisciplinary collaborations of life sciences, computational and mathematical sciences, systems engineering, and analytical technology, etc. For analytical chemistry, developing innovative methods to meet the requirement of systems biology represents new challenges as also opportunities and responsibility. In this review, systems biology-oriented micro-separation technologies are introduced for comprehensive profiling of genome, proteome and metabolome, characterization of biomolecules interaction and single cell analysis such as capillary electrophoresis, ultra-thin layer gel electrophoresis, micro-column liquid chromatography, and their multidimensional combinations, parallel integrations, microfabricated formats, and nano technology involvement. Future challenges and directions are also suggested.

  1. Tiny cells meet big questions: a closer look at bacterial cell biology.

    Science.gov (United States)

    Goley, Erin D

    2013-04-01

    While studying actin assembly as a graduate student with Matt Welch at the University of California at Berkeley, my interest was piqued by reports of surprising observations in bacteria: the identification of numerous cytoskeletal proteins, actin homologues fulfilling spindle-like functions, and even the presence of membrane-bound organelles. Curiosity about these phenomena drew me to Lucy Shapiro's lab at Stanford University for my postdoctoral research. In the Shapiro lab, and now in my lab at Johns Hopkins, I have focused on investigating the mechanisms of bacterial cytokinesis. Spending time as both a eukaryotic cell biologist and a bacterial cell biologist has convinced me that bacterial cells present the same questions as eukaryotic cells: How are chromosomes organized and accurately segregated? How is force generated for cytokinesis? How is polarity established? How are signals transduced within and between cells? These problems are conceptually similar between eukaryotes and bacteria, although their solutions can differ significantly in specifics. In this Perspective, I provide a broad view of cell biological phenomena in bacteria, the technical challenges facing those of us who peer into bacterial cells, and areas of common ground as research in eukaryotic and bacterial cell biology moves forward.

  2. Knowledge Gaps in Rodent Pancreas Biology: Taking Human Pluripotent Stem Cell-Derived Pancreatic Beta Cells into Our Own Hands.

    Science.gov (United States)

    Santosa, Munirah Mohamad; Low, Blaise Su Jun; Pek, Nicole Min Qian; Teo, Adrian Kee Keong

    2015-01-01

    In the field of stem cell biology and diabetes, we and others seek to derive mature and functional human pancreatic β cells for disease modeling and cell replacement therapy. Traditionally, knowledge gathered from rodents is extended to human pancreas developmental biology research involving human pluripotent stem cells (hPSCs). While much has been learnt from rodent pancreas biology in the early steps toward Pdx1(+) pancreatic progenitors, much less is known about the transition toward Ngn3(+) pancreatic endocrine progenitors. Essentially, the later steps of pancreatic β cell development and maturation remain elusive to date. As a result, the most recent advances in the stem cell and diabetes field have relied upon combinatorial testing of numerous growth factors and chemical compounds in an arbitrary trial-and-error fashion to derive mature and functional human pancreatic β cells from hPSCs. Although this hit-or-miss approach appears to have made some headway in maturing human pancreatic β cells in vitro, its underlying biology is vaguely understood. Therefore, in this mini-review, we discuss some of these late-stage signaling pathways that are involved in human pancreatic β cell differentiation and highlight our current understanding of their relevance in rodent pancreas biology. Our efforts here unravel several novel signaling pathways that can be further studied to shed light on unexplored aspects of rodent pancreas biology. New investigations into these signaling pathways are expected to advance our knowledge in human pancreas developmental biology and to aid in the translation of stem cell biology in the context of diabetes treatments.

  3. Biology and flow cytometry of proangiogenic hematopoietic progenitors cells.

    Science.gov (United States)

    Rose, Jonathan A; Erzurum, Serpil; Asosingh, Kewal

    2015-01-01

    During development, hematopoiesis and neovascularization are closely linked to each other via a common bipotent stem cell called the hemangioblast that gives rise to both hematopoietic cells and endothelial cells. In postnatal life, this functional connection between the vasculature and hematopoiesis is maintained by a subset of hematopoietic progenitor cells endowed with the capacity to differentiate into potent proangiogenic cells. These proangiogenic hematopoietic progenitors comprise a specific subset of bone marrow (BM)-derived cells that homes to sites of neovascularization and possess potent paracrine angiogenic activity. There is emerging evidence that this subpopulation of hematopoietic progenitors plays a critical role in vascular health and disease. Their angiogenic activity is distinct from putative "endothelial progenitor cells" that become structural cells of the endothelium by differentiation into endothelial cells. Proangiogenic hematopoietic progenitor cell research requires multidisciplinary expertise in flow cytometry, hematology, and vascular biology. This review provides a comprehensive overview of proangiogenic hematopoietic progenitor cell biology and flow cytometric methods to detect these cells in the peripheral blood circulation and BM. © 2014 International Society for Advancement of Cytometry.

  4. On the Modelling of Biological Patterns with Mechanochemical Models: Insights from Analysis and Computation

    KAUST Repository

    Moreo, P.

    2009-11-14

    The diversity of biological form is generated by a relatively small number of underlying mechanisms. Consequently, mathematical and computational modelling can, and does, provide insight into how cellular level interactions ultimately give rise to higher level structure. Given cells respond to mechanical stimuli, it is therefore important to consider the effects of these responses within biological self-organisation models. Here, we consider the self-organisation properties of a mechanochemical model previously developed by three of the authors in Acta Biomater. 4, 613-621 (2008), which is capable of reproducing the behaviour of a population of cells cultured on an elastic substrate in response to a variety of stimuli. In particular, we examine the conditions under which stable spatial patterns can emerge with this model, focusing on the influence of mechanical stimuli and the interplay of non-local phenomena. To this end, we have performed a linear stability analysis and numerical simulations based on a mixed finite element formulation, which have allowed us to study the dynamical behaviour of the system in terms of the qualitative shape of the dispersion relation. We show that the consideration of mechanotaxis, namely changes in migration speeds and directions in response to mechanical stimuli alters the conditions for pattern formation in a singular manner. Furthermore without non-local effects, responses to mechanical stimuli are observed to result in dispersion relations with positive growth rates at arbitrarily large wavenumbers, in turn yielding heterogeneity at the cellular level in model predictions. This highlights the sensitivity and necessity of non-local effects in mechanically influenced biological pattern formation models and the ultimate failure of the continuum approximation in their absence. © 2009 Society for Mathematical Biology.

  5. Cell adhesive ability of a biological foam ceramic with surface modification

    International Nuclear Information System (INIS)

    Zhang Yong; Li Xiaoyu; Feng Fan; Lin Yunfeng; Liao Yunmao; Tian, Weidong; Liu Lei

    2008-01-01

    Biological foam ceramic is a promising material for tissue engineering scaffold because of its biocompatibility, biodegradation and adequate pores measured from micrometer to nanometers. The aim of this study was to evaluate the adhesion and proliferation of adipose-derived stromal cells (ADSCs) on the biological foam ceramic coated with fibronectin. ADSCs were harvested from SD rats and passaged three times prior to seeding onto biological foam surface modified with fibronectin (50 μg/ml). Scaffold without surface modification served as control. To characterize cellular attachment, cells were incubated on the scaffold for 1 h and 3 h and then the cells attached onto the scaffold were counted. The difference of proliferation was appraised using MTT assay at day 1, 3, 5 and 7 before the cells reached confluence. After 7 days of culture, scanning electron microscope (SEM) was chosen to assess cell morphology and attachment of ADSCs on the biological foam ceramic. Attachment of ADSCs on the biological foam ceramic surface modified with fibronectin at 1 h or 3 h was substantially greater than that in control. MTT assay revealed that ADSCs proliferation tendency of the experimental group was nearly parallel to that of control. SEM view showed that ADSCs in the experimental groups connected more tightly and excreted more collagen than that in control. The coating of fibronectin could improve the cell adhesive ability of biological foam ceramics without evident effect on proliferation

  6. Compact Electro-Permeabilization System for Controlled Treatment of Biological Cells and Cell Medium Conductivity Change Measurement

    Directory of Open Access Journals (Sweden)

    Novickij Vitalij

    2014-10-01

    Full Text Available Subjection of biological cells to high intensity pulsed electric field results in the permeabilization of the cell membrane. Measurement of the electrical conductivity change allows an analysis of the dynamics of the process, determination of the permeabilization thresholds, and ion efflux influence. In this work a compact electro-permeabilization system for controlled treatment of biological cells is presented. The system is capable of delivering 5 μs - 5 ms repetitive square wave electric field pulses with amplitude up to 1 kV. Evaluation of the cell medium conductivity change is implemented in the setup, allowing indirect measurement of the ion concentration changes occurring due to the cell membrane permeabilization. The simulation model using SPICE and the experimental data of the proposed system are presented in this work. Experimental data with biological cells is also overviewed

  7. Virtual Reconstruction and Three-Dimensional Printing of Blood Cells as a Tool in Cell Biology Education.

    Science.gov (United States)

    Augusto, Ingrid; Monteiro, Douglas; Girard-Dias, Wendell; Dos Santos, Thaisa Oliveira; Rosa Belmonte, Simone Letícia; Pinto de Oliveira, Jairo; Mauad, Helder; da Silva Pacheco, Marcos; Lenz, Dominik; Stefanon Bittencourt, Athelson; Valentim Nogueira, Breno; Lopes Dos Santos, Jorge Roberto; Miranda, Kildare; Guimarães, Marco Cesar Cunegundes

    2016-01-01

    The cell biology discipline constitutes a highly dynamic field whose concepts take a long time to be incorporated into the educational system, especially in developing countries. Amongst the main obstacles to the introduction of new cell biology concepts to students is their general lack of identification with most teaching methods. The introduction of elaborated figures, movies and animations to textbooks has given a tremendous contribution to the learning process and the search for novel teaching methods has been a central goal in cell biology education. Some specialized tools, however, are usually only available in advanced research centers or in institutions that are traditionally involved with the development of novel teaching/learning processes, and are far from becoming reality in the majority of life sciences schools. When combined with the known declining interest in science among young people, a critical scenario may result. This is especially important in the field of electron microscopy and associated techniques, methods that have greatly contributed to the current knowledge on the structure and function of different cell biology models but are rarely made accessible to most students. In this work, we propose a strategy to increase the engagement of students into the world of cell and structural biology by combining 3D electron microscopy techniques and 3D prototyping technology (3D printing) to generate 3D physical models that accurately and realistically reproduce a close-to-the native structure of the cell and serve as a tool for students and teachers outside the main centers. We introduce three strategies for 3D imaging, modeling and prototyping of cells and propose the establishment of a virtual platform where different digital models can be deposited by EM groups and subsequently downloaded and printed in different schools, universities, research centers and museums, thereby modernizing teaching of cell biology and increasing the accessibility to

  8. Introducing the RadBioStat Educational Software: Computer-Assisted Teaching of the Random Nature of Cell Killing

    Directory of Open Access Journals (Sweden)

    Safari A

    2014-06-01

    Full Text Available The interaction of radiation with cells and tissues has a random nature. Therefore, understanding the random nature of cell killing that is determined by Poisson distribution statistics is an essential point in education of radiation biology. RadBioStat is a newly developed educational MATLAB-based software designed for computer-assisted learning of the target theory in radiation biology. Although its potential applications is developing rapidly, currently RadBioStat software can be a useful tool in computerassisted education of radiobiological models such as single target single hit, multiple target single hit and multiple target multiple hit. Scholars’ feedback is valuable to the producers of this software and help them continuously improve this product, add new features and increase its desirability and functionality.

  9. Muscle Satellite Cells: Exploring the Basic Biology to Rule Them.

    Science.gov (United States)

    Almeida, Camila F; Fernandes, Stephanie A; Ribeiro Junior, Antonio F; Keith Okamoto, Oswaldo; Vainzof, Mariz

    2016-01-01

    Adult skeletal muscle is a postmitotic tissue with an enormous capacity to regenerate upon injury. This is accomplished by resident stem cells, named satellite cells, which were identified more than 50 years ago. Since their discovery, many researchers have been concentrating efforts to answer questions about their origin and role in muscle development, the way they contribute to muscle regeneration, and their potential to cell-based therapies. Satellite cells are maintained in a quiescent state and upon requirement are activated, proliferating, and fusing with other cells to form or repair myofibers. In addition, they are able to self-renew and replenish the stem pool. Every phase of satellite cell activity is highly regulated and orchestrated by many molecules and signaling pathways; the elucidation of players and mechanisms involved in satellite cell biology is of extreme importance, being the first step to expose the crucial points that could be modulated to extract the optimal response from these cells in therapeutic strategies. Here, we review the basic aspects about satellite cells biology and briefly discuss recent findings about therapeutic attempts, trying to raise questions about how basic biology could provide a solid scaffold to more successful use of these cells in clinics.

  10. Plasma cell leukemia: update on biology and therapy.

    Science.gov (United States)

    Mina, Roberto; D'Agostino, Mattia; Cerrato, Chiara; Gay, Francesca; Palumbo, Antonio

    2017-07-01

    Plasma cell leukemia (PCL) is a rare, but very aggressive, plasma cell dyscrasia, representing a distinct clinicopathological entity as compared to multiple myeloma (MM), with peculiar biological and clinical features. A hundred times rarer than MM, the disease course is characterized by short remissions and poor survival. PCL is defined by an increased percentage (>20%) and absolute number (>2 × 10 9 /l) of plasma cells in the peripheral blood. PCL is defined as 'primary' when peripheral plasmacytosis is detected at diagnosis, 'secondary' when leukemization occurs in a patient with preexisting MM. Novel agents have revolutionized the outcomes of MM patients and have been introduced also for the treatment of PCL. Here, we provide an update on biology and treatment options for PCL.

  11. Integrating biological redesign: where synthetic biology came from and where it needs to go.

    Science.gov (United States)

    Way, Jeffrey C; Collins, James J; Keasling, Jay D; Silver, Pamela A

    2014-03-27

    Synthetic biology seeks to extend approaches from engineering and computation to redesign of biology, with goals such as generating new chemicals, improving human health, and addressing environmental issues. Early on, several guiding principles of synthetic biology were articulated, including design according to specification, separation of design from fabrication, use of standardized biological parts and organisms, and abstraction. We review the utility of these principles over the past decade in light of the field's accomplishments in building complex systems based on microbial transcription and metabolism and describe the progress in mammalian cell engineering. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. Multispectral optical tweezers for molecular diagnostics of single biological cells

    Science.gov (United States)

    Butler, Corey; Fardad, Shima; Sincore, Alex; Vangheluwe, Marie; Baudelet, Matthieu; Richardson, Martin

    2012-03-01

    Optical trapping of single biological cells has become an established technique for controlling and studying fundamental behavior of single cells with their environment without having "many-body" interference. The development of such an instrument for optical diagnostics (including Raman and fluorescence for molecular diagnostics) via laser spectroscopy with either the "trapping" beam or secondary beams is still in progress. This paper shows the development of modular multi-spectral imaging optical tweezers combining Raman and Fluorescence diagnostics of biological cells.

  13. "Known Unknowns": Current Questions in Muscle Satellite Cell Biology.

    Science.gov (United States)

    Cornelison, Ddw

    2018-01-01

    Our understanding of satellite cells, now known to be the obligate stem cells of skeletal muscle, has increased dramatically in recent years due to the introduction of new molecular, genetic, and technical resources. In addition to their role in acute repair of damaged muscle, satellite cells are of interest in the fields of aging, exercise, neuromuscular disease, and stem cell therapy, and all of these applications have driven a dramatic increase in our understanding of the activity and potential of satellite cells. However, many fundamental questions of satellite cell biology remain to be answered, including their emergence as a specific lineage, the degree and significance of heterogeneity within the satellite cell population, the roles of their interactions with other resident and infiltrating cell types during homeostasis and regeneration, and the relative roles of intrinsic vs extrinsic factors that may contribute to satellite cell dysfunction in the context of aging or disease. This review will address the current state of these open questions in satellite cell biology. © 2018 Elsevier Inc. All rights reserved.

  14. Mobile Applications in Cell Biology Present New Approaches for Cell Modelling

    Science.gov (United States)

    de Oliveira, Mayara Lustosa; Galembeck, Eduardo

    2016-01-01

    Cell biology apps were surveyed in order to identify whether there are new approaches for modelling cells allowed by the new technologies implemented in tablets and smartphones. A total of 97 apps were identified in 3 stores surveyed (Apple, Google Play and Amazon), they are presented as: education 48.4%, games 26.8% and medicine 15.4%. The apps…

  15. Prototype Biology-Based Radiation Risk Module Project

    Science.gov (United States)

    Terrier, Douglas; Clayton, Ronald G.; Patel, Zarana; Hu, Shaowen; Huff, Janice

    2015-01-01

    Biological effects of space radiation and risk mitigation are strategic knowledge gaps for the Evolvable Mars Campaign. The current epidemiology-based NASA Space Cancer Risk (NSCR) model contains large uncertainties (HAT #6.5a) due to lack of information on the radiobiology of galactic cosmic rays (GCR) and lack of human data. The use of experimental models that most accurately replicate the response of human tissues is critical for precision in risk projections. Our proposed study will compare DNA damage, histological, and cell kinetic parameters after irradiation in normal 2D human cells versus 3D tissue models, and it will use a multi-scale computational model (CHASTE) to investigate various biological processes that may contribute to carcinogenesis, including radiation-induced cellular signaling pathways. This cross-disciplinary work, with biological validation of an evolvable mathematical computational model, will help reduce uncertainties within NSCR and aid risk mitigation for radiation-induced carcinogenesis.

  16. The species translation challenge-a systems biology perspective on human and rat bronchial epithelial cells.

    Science.gov (United States)

    Poussin, Carine; Mathis, Carole; Alexopoulos, Leonidas G; Messinis, Dimitris E; Dulize, Rémi H J; Belcastro, Vincenzo; Melas, Ioannis N; Sakellaropoulos, Theodore; Rhrissorrakrai, Kahn; Bilal, Erhan; Meyer, Pablo; Talikka, Marja; Boué, Stéphanie; Norel, Raquel; Rice, John J; Stolovitzky, Gustavo; Ivanov, Nikolai V; Peitsch, Manuel C; Hoeng, Julia

    2014-01-01

    The biological responses to external cues such as drugs, chemicals, viruses and hormones, is an essential question in biomedicine and in the field of toxicology, and cannot be easily studied in humans. Thus, biomedical research has continuously relied on animal models for studying the impact of these compounds and attempted to 'translate' the results to humans. In this context, the SBV IMPROVER (Systems Biology Verification for Industrial Methodology for PROcess VErification in Research) collaborative initiative, which uses crowd-sourcing techniques to address fundamental questions in systems biology, invited scientists to deploy their own computational methodologies to make predictions on species translatability. A multi-layer systems biology dataset was generated that was comprised of phosphoproteomics, transcriptomics and cytokine data derived from normal human (NHBE) and rat (NRBE) bronchial epithelial cells exposed in parallel to more than 50 different stimuli under identical conditions. The present manuscript describes in detail the experimental settings, generation, processing and quality control analysis of the multi-layer omics dataset accessible in public repositories for further intra- and inter-species translation studies.

  17. The species translation challenge—A systems biology perspective on human and rat bronchial epithelial cells

    Science.gov (United States)

    Poussin, Carine; Mathis, Carole; Alexopoulos, Leonidas G; Messinis, Dimitris E; Dulize, Rémi H J; Belcastro, Vincenzo; Melas, Ioannis N; Sakellaropoulos, Theodore; Rhrissorrakrai, Kahn; Bilal, Erhan; Meyer, Pablo; Talikka, Marja; Boué, Stéphanie; Norel, Raquel; Rice, John J; Stolovitzky, Gustavo; Ivanov, Nikolai V; Peitsch, Manuel C; Hoeng, Julia

    2014-01-01

    The biological responses to external cues such as drugs, chemicals, viruses and hormones, is an essential question in biomedicine and in the field of toxicology, and cannot be easily studied in humans. Thus, biomedical research has continuously relied on animal models for studying the impact of these compounds and attempted to ‘translate’ the results to humans. In this context, the SBV IMPROVER (Systems Biology Verification for Industrial Methodology for PROcess VErification in Research) collaborative initiative, which uses crowd-sourcing techniques to address fundamental questions in systems biology, invited scientists to deploy their own computational methodologies to make predictions on species translatability. A multi-layer systems biology dataset was generated that was comprised of phosphoproteomics, transcriptomics and cytokine data derived from normal human (NHBE) and rat (NRBE) bronchial epithelial cells exposed in parallel to more than 50 different stimuli under identical conditions. The present manuscript describes in detail the experimental settings, generation, processing and quality control analysis of the multi-layer omics dataset accessible in public repositories for further intra- and inter-species translation studies. PMID:25977767

  18. Nanobiotechnology meets plant cell biology: Carbon nanotubes as organelle targeting nanocarriers

    KAUST Repository

    Serag, Maged F.; Kaji, Noritada; Habuchi, Satoshi; Bianco, Alberto; Baba, Yoshinobu

    2013-01-01

    For years, nanotechnology has shown great promise in the fields of biomedical and biotechnological sciences and medical research. In this review, we demonstrate its versatility and applicability in plant cell biology studies. Specifically, we discuss the ability of functionalized carbon nanotubes to penetrate the plant cell wall, target specific organelles, probe protein-carrier activity and induce organelle recycling in plant cells. We also, shed light on prospective applications of carbon nanomaterials in cell biology and plant cell transformation. © 2013 The Royal Society of Chemistry.

  19. Nanomaterials modulate stem cell differentiation: biological interaction and underlying mechanisms.

    Science.gov (United States)

    Wei, Min; Li, Song; Le, Weidong

    2017-10-25

    Stem cells are unspecialized cells that have the potential for self-renewal and differentiation into more specialized cell types. The chemical and physical properties of surrounding microenvironment contribute to the growth and differentiation of stem cells and consequently play crucial roles in the regulation of stem cells' fate. Nanomaterials hold great promise in biological and biomedical fields owing to their unique properties, such as controllable particle size, facile synthesis, large surface-to-volume ratio, tunable surface chemistry, and biocompatibility. Over the recent years, accumulating evidence has shown that nanomaterials can facilitate stem cell proliferation and differentiation, and great effort is undertaken to explore their possible modulating manners and mechanisms on stem cell differentiation. In present review, we summarize recent progress in the regulating potential of various nanomaterials on stem cell differentiation and discuss the possible cell uptake, biological interaction and underlying mechanisms.

  20. The bottom-up approach to defining life : deciphering the functional organization of biological cells via multi-objective representation of biological complexity from molecules to cells

    Directory of Open Access Journals (Sweden)

    Sathish ePeriyasamy

    2013-12-01

    Full Text Available In silico representation of cellular systems needs to represent the adaptive dynamics of biological cells, recognizing a cell’s multi-objective topology formed by spatially and temporally cohesive intracellular structures. The design of these models needs to address the hierarchical and concurrent nature of cellular functions and incorporate the ability to self-organise in response to transitions between healthy and pathological phases, and adapt accordingly. The functions of biological systems are constantly evolving, due to the ever changing demands of their environment. Biological systems meet these demands by pursuing objectives, aided by their constituents, giving rise to biological functions. A biological cell is organised into an objective/task hierarchy. These objective hierarchy corresponds to the nested nature of temporally cohesive structures and representing them will facilitate in studying pleiotropy and polygeny by modeling causalities propagating across multiple interconnected intracellular processes. Although biological adaptations occur in physiological, developmental and reproductive timescales, the paper is focused on adaptations that occur within physiological timescales, where the biomolecular activities contributing to functional organisation, play a key role in cellular physiology. The paper proposes a multi-scale and multi-objective modelling approach from the bottom-up by representing temporally cohesive structures for multi-tasking of intracellular processes. Further the paper characterises the properties and constraints that are consequential to the organisational and adaptive dynamics in biological cells.

  1. Computer modeling in developmental biology: growing today, essential tomorrow.

    Science.gov (United States)

    Sharpe, James

    2017-12-01

    D'Arcy Thompson was a true pioneer, applying mathematical concepts and analyses to the question of morphogenesis over 100 years ago. The centenary of his famous book, On Growth and Form , is therefore a great occasion on which to review the types of computer modeling now being pursued to understand the development of organs and organisms. Here, I present some of the latest modeling projects in the field, covering a wide range of developmental biology concepts, from molecular patterning to tissue morphogenesis. Rather than classifying them according to scientific question, or scale of problem, I focus instead on the different ways that modeling contributes to the scientific process and discuss the likely future of modeling in developmental biology. © 2017. Published by The Company of Biologists Ltd.

  2. Cells from icons to symbols: molecularizing cell biology in the 1980s.

    Science.gov (United States)

    Serpente, Norberto

    2011-12-01

    Over centuries cells have been the target of optical and electronic microscopes as well as others technologies, with distinctive types of visual output. Whilst optical technologies produce images 'evident to the eye', the electronic and especially the molecular create images that are more elusive to conceptualization and assessment. My study applies the semiotic approach to the production of images in cell biology to capture the shift from microscopic images to non-traditional visual technologies around 1980. Here I argue that the visual shift that coincides with the growing dominance of molecular biology involves a change from iconic to symbolic forms. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. The central dogma of cell biology.

    Science.gov (United States)

    Cooper, S

    1981-06-01

    The Continuum Model proposes that preparations for DNA synthesis occur continuously during all phases of the division cycle. Various stimuli activate cell proliferation by changing the rate of initiator (protein) synthesis. Cell division does not initiate any process regulating cell proliferation. Cell division is the end of a process and the beginning of nothing. The alternative model which has cell proliferation regulated in the G1 phase of the division cycle is reexamined and the two types of evidence for this model, G1-variability and G1-arrest are shown to be compatible with the Continuum Model. Here, the Continuum Model is generalized to produce a new look at the logic of the division cycle in prokaryotes and eukaryotes. This new view, the Central Dogma of Cell Biology, is presented and two predictions are made. I propose that (i) cell division does not have any regulatory function, and (ii) that DNA synthesis may, indeed, have some affect on the synthesis of initiator.

  4. Discovery of HeLa Cell Contamination in HES Cells: Call for Cell Line Authentication in Reproductive Biology Research.

    Science.gov (United States)

    Kniss, Douglas A; Summerfield, Taryn L

    2014-08-01

    Continuous cell lines are used frequently in reproductive biology research to study problems in early pregnancy events and parturition. It has been recognized for 50 years that many mammalian cell lines contain inter- or intraspecies contaminations with other cells. However, most investigators do not routinely test their culture systems for cross-contamination. The most frequent contributor to cross-contamination of cell lines is the HeLa cell isolated from an aggressive cervical adenocarcinoma. We report on the discovery of HeLa cell contamination of the human endometrial epithelial cell line HES isolated in our laboratory. Short tandem repeat analysis of 9 unique genetic loci demonstrated molecular identity between HES and HeLa cells. In addition, we verified that WISH cells, isolated originally from human amnion epithelium, were also contaminated with HeLa cells. Inasmuch as our laboratory did not culture HeLa cells at the time of HES cell derivations, the source of contamination was the WISH cell line. These data highlight the need for continued diligence in authenticating cell lines used in reproductive biology research. © The Author(s) 2014.

  5. Biophysical mechanisms complementing "classical" cell biology.

    Science.gov (United States)

    Funk, Richard H W

    2018-01-01

    This overview addresses phenomena in cell- and molecular biology which are puzzling by their fast and highly coordinated way of organization. Generally, it appears that informative processes probably involved are more on the biophysical than on the classical biochemical side. The coordination problem is explained within the first part of the review by the topic of endogenous electrical phenomena. These are found e.g. in fast tissue organization and reorganization processes like development, wound healing and regeneration. Here, coupling into classical biochemical signaling and reactions can be shown by modern microscopy, electronics and bioinformatics. Further, one can follow the triggered reactions seamlessly via molecular biology till into genetics. Direct observation of intracellular electric processes is very difficult because of e.g. shielding through the cell membrane and damping by other structures. Therefore, we have to rely on photonic and photon - phonon coupling phenomena like molecular vibrations, which are addressed within the second part. Molecules normally possess different charge moieties and thus small electromagnetic (EMF) patterns arise during molecular vibration. These patterns can now be measured best within the optical part of the spectrum - much less in the lower terahertz till kHz and lower Hz part (third part of this review). Finally, EMFs facilitate quantum informative processes in coherent domains of molecular, charge and electron spin motion. This helps to coordinate such manifold and intertwined processes going on within cells, tissues and organs (part 4). Because the phenomena described in part 3 and 4 of the review still await really hard proofs we need concerted efforts and a combination of biophysics, molecular biology and informatics to unravel the described mysteries in "physics of life".

  6. Mathematical computer simulation of the process of ultrasound interaction with biological medium

    International Nuclear Information System (INIS)

    Yakovleva, T.; Nassiri, D.; Ciantar, D.

    1996-01-01

    The aim of the paper is to study theoretically the interaction of ultrasound irradiation with biological medium and the peculiarities of ultrasound scattering by inhomogeneities of biological tissue, which can be represented by fractal structures. This investigation has been used for the construction of the computer model of three-dimensional ultrasonic imaging system what gives the possibility to define more accurately the pathological changes in such a tissue by means of its image analysis. Poster 180. (author)

  7. Getting the measure of things: the physical biology of stem cells.

    Science.gov (United States)

    Lowell, Sally

    2013-10-01

    In July 2013, the diverse fields of biology, physics and mathematics converged to discuss 'The Physical Biology of Stem Cells', the subject of the third annual symposium of the Cambridge Stem Cell Institute, UK. Two clear themes resonated throughout the meeting: the new insights gained from advances in the acquisition and interpretation of quantitative data; and the importance of 'thinking outside the nucleus' to consider physical influences on cell fate.

  8. Tensegrity I. Cell structure and hierarchical systems biology

    Science.gov (United States)

    Ingber, Donald E.

    2003-01-01

    In 1993, a Commentary in this journal described how a simple mechanical model of cell structure based on tensegrity architecture can help to explain how cell shape, movement and cytoskeletal mechanics are controlled, as well as how cells sense and respond to mechanical forces (J. Cell Sci. 104, 613-627). The cellular tensegrity model can now be revisited and placed in context of new advances in our understanding of cell structure, biological networks and mechanoregulation that have been made over the past decade. Recent work provides strong evidence to support the use of tensegrity by cells, and mathematical formulations of the model predict many aspects of cell behavior. In addition, development of the tensegrity theory and its translation into mathematical terms are beginning to allow us to define the relationship between mechanics and biochemistry at the molecular level and to attack the larger problem of biological complexity. Part I of this two-part article covers the evidence for cellular tensegrity at the molecular level and describes how this building system may provide a structural basis for the hierarchical organization of living systems--from molecule to organism. Part II, which focuses on how these structural networks influence information processing networks, appears in the next issue.

  9. MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

    Science.gov (United States)

    Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

    2016-01-01

    Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

  10. Synthetic biology in mammalian cells: Next generation research tools and therapeutics

    Science.gov (United States)

    Lienert, Florian; Lohmueller, Jason J; Garg, Abhishek; Silver, Pamela A

    2014-01-01

    Recent progress in DNA manipulation and gene circuit engineering has greatly improved our ability to programme and probe mammalian cell behaviour. These advances have led to a new generation of synthetic biology research tools and potential therapeutic applications. Programmable DNA-binding domains and RNA regulators are leading to unprecedented control of gene expression and elucidation of gene function. Rebuilding complex biological circuits such as T cell receptor signalling in isolation from their natural context has deepened our understanding of network motifs and signalling pathways. Synthetic biology is also leading to innovative therapeutic interventions based on cell-based therapies, protein drugs, vaccines and gene therapies. PMID:24434884

  11. Progenitor cells in the kidney: biology and therapeutic perspectives

    NARCIS (Netherlands)

    Rookmaaker, M.B.; Verhaar, M.C.; Zonneveld, A.J. van; Rabelink, T.J.

    2004-01-01

    Progenitor cells in the kidney: Biology and therapeutic perspectives. The stem cell may be viewed as an engineer who can read the blue print and become the building. The role of this fascinating cell in physiology and pathophysiology has recently attracted a great deal of interest. The archetype of

  12. Alkali-treated titanium selectively regulating biological behaviors of bacteria, cancer cells and mesenchymal stem cells.

    Science.gov (United States)

    Li, Jinhua; Wang, Guifang; Wang, Donghui; Wu, Qianju; Jiang, Xinquan; Liu, Xuanyong

    2014-12-15

    Many attentions have been paid to the beneficial effect of alkali-treated titanium to bioactivity and osteogenic activity, but few to the other biological effect. In this work, hierarchical micro/nanopore films were prepared on titanium surface by acid etching and alkali treatment and their biological effects on bacteria, cancer cells and mesenchymal stem cells were investigated. Gram-positive Staphylococcus aureus, Gram-negative Escherichia coli, and human cholangiocarcinoma cell line RBE were used to investigate whether alkali-treated titanium can influence behaviors of bacteria and cancer cells. Responses of bone marrow mesenchymal stem cells (BMMSCs) to alkali-treated titanium were also subsequently investigated. The alkali-treated titanium can potently reduce bacterial adhesion, inhibit RBE and BMMSCs proliferation, while can better promote BMMSCs osteogenesis and angiogenesis than acid-etched titanium. The bacteriostatic ability of the alkali-treated titanium is proposed to result from the joint effect of micro/nanotopography and local pH increase at bacterium/material interface due to the hydrolysis of alkali (earth) metal titanate salts. The inhibitory action of cell proliferation is thought to be the effect of local pH increase at cell/material interface which causes the alkalosis of cells. This alkalosis model reported in this work will help to understand the biologic behaviors of various cells on alkali-treated titanium surface and design the intended biomedical applications. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. AFM Nanotools for Surgery of Biological Cells

    Energy Technology Data Exchange (ETDEWEB)

    Beard, J D; Gordeev, S N [Department of Physics, Claverton Down, University of Bath, Bath, BA2 7AY (United Kingdom); Guy, R H, E-mail: jdb28@bath.ac.uk [Department of Pharmacy and Pharmacology, Claverton Down, University of Bath, Bath, BA2 7AY (United Kingdom)

    2011-03-01

    Using a method of electron-beam induced deposition, we have been able to fabricate specialized AFM probes with application as 'nanotools' for the manipulation of biological structures ('nanosurgery'). We describe several such tools, including a 'nanoscalpel', 'nanoneedles' for probing intracellular structures, and a 'nanotome' which can separate surface layers from a biological structure. These applications are demonstrated by performing nanomanipulation on corneocyte cells from the outer layer of human skin.

  14. Implications of Big Data for cell biology

    OpenAIRE

    Dolinski, Kara; Troyanskaya, Olga G.

    2015-01-01

    “Big Data” has surpassed “systems biology” and “omics” as the hottest buzzword in the biological sciences, but is there any substance behind the hype? Certainly, we have learned about various aspects of cell and molecular biology from the many individual high-throughput data sets that have been published in the past 15–20 years. These data, although useful as individual data sets, can provide much more knowledge when interrogated with Big Data approaches, such as applying integrative methods ...

  15. Periodicity computation of generalized mathematical biology problems involving delay differential equations.

    Science.gov (United States)

    Jasim Mohammed, M; Ibrahim, Rabha W; Ahmad, M Z

    2017-03-01

    In this paper, we consider a low initial population model. Our aim is to study the periodicity computation of this model by using neutral differential equations, which are recognized in various studies including biology. We generalize the neutral Rayleigh equation for the third-order by exploiting the model of fractional calculus, in particular the Riemann-Liouville differential operator. We establish the existence and uniqueness of a periodic computational outcome. The technique depends on the continuation theorem of the coincidence degree theory. Besides, an example is presented to demonstrate the finding.

  16. Computational methods for three-dimensional microscopy reconstruction

    CERN Document Server

    Frank, Joachim

    2014-01-01

    Approaches to the recovery of three-dimensional information on a biological object, which are often formulated or implemented initially in an intuitive way, are concisely described here based on physical models of the object and the image-formation process. Both three-dimensional electron microscopy and X-ray tomography can be captured in the same mathematical framework, leading to closely-related computational approaches, but the methodologies differ in detail and hence pose different challenges. The editors of this volume, Gabor T. Herman and Joachim Frank, are experts in the respective methodologies and present research at the forefront of biological imaging and structural biology.   Computational Methods for Three-Dimensional Microscopy Reconstruction will serve as a useful resource for scholars interested in the development of computational methods for structural biology and cell biology, particularly in the area of 3D imaging and modeling.

  17. Fluid models and simulations of biological cell phenomena

    Science.gov (United States)

    Greenspan, H. P.

    1982-01-01

    The dynamics of coated droplets are examined within the context of biofluids. Of specific interest is the manner in which the shape of a droplet, the motion within it as well as that of aggregates of droplets can be controlled by the modulation of surface properties and the extent to which such fluid phenomena are an intrinsic part of cellular processes. From the standpoint of biology, an objective is to elucidate some of the general dynamical features that affect the disposition of an entire cell, cell colonies and tissues. Conventionally averaged field variables of continuum mechanics are used to describe the overall global effects which result from the myriad of small scale molecular interactions. An attempt is made to establish cause and effect relationships from correct dynamical laws of motion rather than by what may have been unnecessary invocation of metabolic or life processes. Several topics are discussed where there are strong analogies droplets and cells including: encapsulated droplets/cell membranes; droplet shape/cell shape; adhesion and spread of a droplet/cell motility and adhesion; and oams and multiphase flows/cell aggregates and tissues. Evidence is presented to show that certain concepts of continuum theory such as suface tension, surface free energy, contact angle, bending moments, etc. are relevant and applicable to the study of cell biology.

  18. The Effects of 3D Computer Simulation on Biology Students' Achievement and Memory Retention

    Science.gov (United States)

    Elangovan, Tavasuria; Ismail, Zurida

    2014-01-01

    A quasi experimental study was conducted for six weeks to determine the effectiveness of two different 3D computer simulation based teaching methods, that is, realistic simulation and non-realistic simulation on Form Four Biology students' achievement and memory retention in Perak, Malaysia. A sample of 136 Form Four Biology students in Perak,…

  19. A decade of molecular cell biology: achievements and challenges.

    Science.gov (United States)

    Akhtar, Asifa; Fuchs, Elaine; Mitchison, Tim; Shaw, Reuben J; St Johnston, Daniel; Strasser, Andreas; Taylor, Susan; Walczak, Claire; Zerial, Marino

    2011-09-23

    Nature Reviews Molecular Cell Biology celebrated its 10-year anniversary during this past year with a series of specially commissioned articles. To complement this, here we have asked researchers from across the field for their insights into how molecular cell biology research has evolved during this past decade, the key concepts that have emerged and the most promising interfaces that have developed. Their comments highlight the broad impact that particular advances have had, some of the basic understanding that we still require, and the collaborative approaches that will be essential for driving the field forward.

  20. Molecular biological features of male germ cell differentiation

    Science.gov (United States)

    HIROSE, MIKA; TOKUHIRO, KEIZO; TAINAKA, HITOSHI; MIYAGAWA, YASUSHI; TSUJIMURA, AKIRA; OKUYAMA, AKIHIKO; NISHIMUNE, YOSHITAKE

    2007-01-01

    Somatic cell differentiation is required throughout the life of a multicellular organism to maintain homeostasis. In contrast, germ cells have only one specific function; to preserve the species by conveying the parental genes to the next generation. Recent studies of the development and molecular biology of the male germ cell have identified many genes, or isoforms, that are specifically expressed in the male germ cell. In the present review, we consider the unique features of male germ cell differentiation. (Reprod Med Biol 2007; 6: 1–9) PMID:29699260

  1. Computer Literacy for Life Sciences: Helping the Digital-Era Biology Undergraduates Face Today's Research

    Science.gov (United States)

    Smolinski, Tomasz G.

    2010-01-01

    Computer literacy plays a critical role in today's life sciences research. Without the ability to use computers to efficiently manipulate and analyze large amounts of data resulting from biological experiments and simulations, many of the pressing questions in the life sciences could not be answered. Today's undergraduates, despite the ubiquity of…

  2. Recent advances in hematopoietic stem cell biology

    DEFF Research Database (Denmark)

    Bonde, Jesper; Hess, David A; Nolta, Jan A

    2004-01-01

    PURPOSE OF REVIEW: Exciting advances have been made in the field of hematopoietic stem cell biology during the past year. This review summarizes recent progress in the identification, culture, and in vivo tracking of hematopoietic stem cells. RECENT FINDINGS: The roles of Wnt and Notch proteins...... in regulating stem cell renewal in the microenvironment, and how these molecules can be exploited in ex vivo stem cell culture, are reviewed. The importance of identification of stem cells using functional as well as phenotypic markers is discussed. The novel field of nanotechnology is then discussed...... in the context of stem cell tracking in vivo. This review concludes with a section on the unexpected potential of bone marrow-derived stem cells to contribute to the repair of damaged tissues. The contribution of cell fusion to explain the latter phenomenon is discussed. SUMMARY: Because of exciting discoveries...

  3. Interdisciplinary research and education at the biology-engineering-computer science interface: a perspective.

    Science.gov (United States)

    Tadmor, Brigitta; Tidor, Bruce

    2005-09-01

    Progress in the life sciences, including genome sequencing and high-throughput experimentation, offers an opportunity for understanding biology and medicine from a systems perspective. This 'new view', which complements the more traditional component-based approach, involves the integration of biological research with approaches from engineering disciplines and computer science. The result is more than a new set of technologies. Rather, it promises a fundamental reconceptualization of the life sciences based on the development of quantitative and predictive models to describe crucial processes. To achieve this change, learning communities are being formed at the interface of the life sciences, engineering and computer science. Through these communities, research and education will be integrated across disciplines and the challenges associated with multidisciplinary team-based science will be addressed.

  4. Cell-free synthetic biology for in vitro prototype engineering.

    Science.gov (United States)

    Moore, Simon J; MacDonald, James T; Freemont, Paul S

    2017-06-15

    Cell-free transcription-translation is an expanding field in synthetic biology as a rapid prototyping platform for blueprinting the design of synthetic biological devices. Exemplar efforts include translation of prototype designs into medical test kits for on-site identification of viruses (Zika and Ebola), while gene circuit cascades can be tested, debugged and re-designed within rapid turnover times. Coupled with mathematical modelling, this discipline lends itself towards the precision engineering of new synthetic life. The next stages of cell-free look set to unlock new microbial hosts that remain slow to engineer and unsuited to rapid iterative design cycles. It is hoped that the development of such systems will provide new tools to aid the transition from cell-free prototype designs to functioning synthetic genetic circuits and engineered natural product pathways in living cells. © 2017 The Author(s).

  5. Highly Resolved Sub-Terahertz Vibrational Spectroscopy of Biological Macromolecules and Bacteria Cells

    Science.gov (United States)

    2016-07-01

    HIGHLY RESOLVED SUB-TERAHERTZ VIBRATIONAL SPECTROSCOPY OF BIOLOGICAL MACROMOLECULES AND BACTERIA CELLS ECBC...SUBTITLE Highly Resolved Sub-Terahertz Vibrational Spectroscopy of Biological Macromolecules and Bacteria Cells 5a. CONTRACT NUMBER W911SR-14-P...22 4.3 Bacteria THz Study

  6. Progress in Cell Marking for Synchrotron X-ray Computed Tomography

    Science.gov (United States)

    Hall, Christopher; Sturm, Erica; Schultke, Elisabeth; Arfelli, Fulvia; Menk, Ralf-Hendrik; Astolfo, Alberto; Juurlink, Bernhard H. J.

    2010-07-01

    Recently there has been an increase in research activity into finding ways of marking cells in live animals for pre-clinical trials. Development of certain drugs and other therapies crucially depend on tracking particular cells or cell types in living systems. Therefore cell marking techniques are required which will enable longitudinal studies, where individuals can be examined several times over the course of a therapy or study. The benefits of being able to study both disease and therapy progression in individuals, rather than cohorts are clear. The need for high contrast 3-D imaging, without harming or altering the biological system requires a non-invasive yet penetrating imaging technique. The technique will also have to provide an appropriate spatial and contrast resolution. X-ray computed tomography offers rapid acquisition of 3-D images and is set to become one of the principal imaging techniques in this area. Work by our group over the last few years has shown that marking cells with gold nano-particles (GNP) is an effective means of visualising marked cells in-vivo using x-ray CT. Here we report the latest results from these studies. Synchrotron X-ray CT images of brain lesions in rats taken using the SYRMEP facility at the Elettra synchrotron in 2009 have been compared with histological examination of the tissues. Some deductions are drawn about the visibility of the gold loaded cells in both light microscopy and x-ray imaging.

  7. A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology

    Science.gov (United States)

    Sung, Myong-Hee

    2013-01-01

    Mathematical modeling of signaling and gene regulatory networks has provided unique insights about systems behaviors for many cell biological problems of medical importance. Quantitative single cell monitoring has a crucial role in advancing systems modeling of molecular networks. However, due to the multidisciplinary techniques that are necessary for adaptation of such systems biology approaches, dissemination to a wide research community has been relatively slow. In this essay, I focus on some technical aspects that are often under-appreciated, yet critical in harnessing live cell imaging methods to achieve single-cell-level understanding and quantitative modeling of molecular networks. The importance of these technical considerations will be elaborated with examples of successes and shortcomings. Future efforts will benefit by avoiding some pitfalls and by utilizing the lessons collectively learned from recent applications of imaging in systems biology. PMID:24709701

  8. Applications of cell-free protein synthesis in synthetic biology: Interfacing bio-machinery with synthetic environments.

    Science.gov (United States)

    Lee, Kyung-Ho; Kim, Dong-Myung

    2013-11-01

    Synthetic biology is built on the synthesis, engineering, and assembly of biological parts. Proteins are the first components considered for the construction of systems with designed biological functions because proteins carry out most of the biological functions and chemical reactions inside cells. Protein synthesis is considered to comprise the most basic levels of the hierarchical structure of synthetic biology. Cell-free protein synthesis has emerged as a powerful technology that can potentially transform the concept of bioprocesses. With the ability to harness the synthetic power of biology without many of the constraints of cell-based systems, cell-free protein synthesis enables the rapid creation of protein molecules from diverse sources of genetic information. Cell-free protein synthesis is virtually free from the intrinsic constraints of cell-based methods and offers greater flexibility in system design and manipulability of biological synthetic machinery. Among its potential applications, cell-free protein synthesis can be combined with various man-made devices for rapid functional analysis of genomic sequences. This review covers recent efforts to integrate cell-free protein synthesis with various reaction devices and analytical platforms. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. New frontiers in human cell biology and medicine: can pluripotent stem cells deliver?

    Science.gov (United States)

    Goldstein, Lawrence S B

    2012-11-12

    Human pluripotent stem cells provide enormous opportunities to treat disease using cell therapy. But human stem cells can also drive biomedical and cell biological discoveries in a human model system, which can be directly linked to understanding disease or developing new therapies. Finally, rigorous scientific studies of these cells can and should inform the many science and medical policy issues that confront the translation of these technologies to medicine. In this paper, I discuss these issues using amyotrophic lateral sclerosis as an example.

  10. ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus

    OpenAIRE

    Karp, P.D.; Berger, B.; Kovats, D.; Lengauer, T.; Linial, M.; Sabeti, P.; Hide, W.; Rost, B.

    2015-01-01

    Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computati...

  11. Induced hemocompatibility and bone formation as biological scaffold for cell therapy implant

    Directory of Open Access Journals (Sweden)

    Keng-Liang Ou

    2016-06-01

    Full Text Available Although stem cells can become almost any type of specialized cell in the human body and may have the potential to generate replacement cells for tissues and organs, the transplantation of these cells are hindered by immune rejection and teratoma formation. However, scientists have found a promising solution for these problems-they have discovered the ability to isolate stem cells from a patient’s umbilical cord blood or bone marrow. Even more recently, small stem cells, such as spore-like stem cells, Blastomere-Like Stem Cells (BLSCs, and Very-Small Embryonic-Like stem cells (VSELs isolated directly from the peripheral blood have beeninvestigated as a novel approach to stem cell therapy as they can be isolated directly from the peripheral blood. A newly-discovered population of multipotent stem cells in this class has been dubbed StemBios (SB cells. The potential therapeutic uses of such stem cells have been explored in many ways, one of which includes dental remodeling and construction. Using adult stem cells, scientists have engineered and cultivated teeth in mice that may one day be used for human implantation.It follows that such regeneration may be possible, to a certain degree, in human patients as well. This idea leads to the present study on the effect of SB cell therapy on early osseointegrationof dental implants. Titanium (Ti dental implants have been proven to be a reliable and predictable treatment for restoration of edentulous regions. The osseointegration process can be described in two stages: primary stability (mechanical stability and secondary stability (biological stability. The mechanical stabilization of the implant reflects the interaction between the bone density and the features of the implant designs and can be determined after implant insertion. Alternatively,the biological stabilization of the implant is a physiologic healing process. It is couple to the biological interaction between the external surface of the

  12. Cancer stem cells in hepatocellular carcinoma: Therapeutic implications based on stem cell biology.

    Science.gov (United States)

    Chiba, Tetsuhiro; Iwama, Atsushi; Yokosuka, Osamu

    2016-01-01

    Hepatocellular carcinoma (HCC) is the sixth most common cancer and the third most frequent cause of cancer-related death worldwide. Despite advances in its diagnosis and treatment, the prognosis of patients with advanced HCC remains unfavorable. Recent advances in stem cell biology and associated technologies have enabled the identification of minor components of tumorigenic cells, termed cancer stem cells (CSC) or tumor-initiating cells, in cancers such as HCC. Furthermore, because CSC play a central role in tumor development, metastasis and recurrence, they are considered to be a therapeutic target in cancer treatment. Hepatic CSC have been successfully identified using functional and cell surface markers. The analysis of purified hepatic CSC has revealed the molecular machinery and signaling pathways involved in their maintenance. In addition, epigenetic transcriptional regulation has been shown to be important in the development and maintenance of CSC. Although inhibitors of CSC show promise as CSC-targeting drugs, novel therapeutic approaches for the eradication of CSC are yet to be established. In this review, we describe recent progress in hepatic CSC research and provide a perspective on the available therapeutic approaches based on stem cell biology. © 2015 The Japan Society of Hepatology.

  13. Quantitative computational models of molecular self-assembly in systems biology.

    Science.gov (United States)

    Thomas, Marcus; Schwartz, Russell

    2017-05-23

    Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

  14. Perturbation biology nominates upstream-downstream drug combinations in RAF inhibitor resistant melanoma cells.

    Science.gov (United States)

    Korkut, Anil; Wang, Weiqing; Demir, Emek; Aksoy, Bülent Arman; Jing, Xiaohong; Molinelli, Evan J; Babur, Özgün; Bemis, Debra L; Onur Sumer, Selcuk; Solit, David B; Pratilas, Christine A; Sander, Chris

    2015-08-18

    Resistance to targeted cancer therapies is an important clinical problem. The discovery of anti-resistance drug combinations is challenging as resistance can arise by diverse escape mechanisms. To address this challenge, we improved and applied the experimental-computational perturbation biology method. Using statistical inference, we build network models from high-throughput measurements of molecular and phenotypic responses to combinatorial targeted perturbations. The models are computationally executed to predict the effects of thousands of untested perturbations. In RAF-inhibitor resistant melanoma cells, we measured 143 proteomic/phenotypic entities under 89 perturbation conditions and predicted c-Myc as an effective therapeutic co-target with BRAF or MEK. Experiments using the BET bromodomain inhibitor JQ1 affecting the level of c-Myc protein and protein kinase inhibitors targeting the ERK pathway confirmed the prediction. In conclusion, we propose an anti-cancer strategy of co-targeting a specific upstream alteration and a general downstream point of vulnerability to prevent or overcome resistance to targeted drugs.

  15. Biomaterials and computation: a strategic alliance to investigate emergent responses of neural cells.

    Science.gov (United States)

    Sergi, Pier Nicola; Cavalcanti-Adam, Elisabetta Ada

    2017-03-28

    Topographical and chemical cues drive migration, outgrowth and regeneration of neurons in different and crucial biological conditions. In the natural extracellular matrix, their influences are so closely coupled that they result in complex cellular responses. As a consequence, engineered biomaterials are widely used to simplify in vitro conditions, disentangling intricate in vivo behaviours, and narrowing the investigation on particular emergent responses. Nevertheless, how topographical and chemical cues affect the emergent response of neural cells is still unclear, thus in silico models are used as additional tools to reproduce and investigate the interactions between cells and engineered biomaterials. This work aims at presenting the synergistic use of biomaterials-based experiments and computation as a strategic way to promote the discovering of complex neural responses as well as to allow the interactions between cells and biomaterials to be quantitatively investigated, fostering a rational design of experiments.

  16. High-dimensional single-cell cancer biology.

    Science.gov (United States)

    Irish, Jonathan M; Doxie, Deon B

    2014-01-01

    Cancer cells are distinguished from each other and from healthy cells by features that drive clonal evolution and therapy resistance. New advances in high-dimensional flow cytometry make it possible to systematically measure mechanisms of tumor initiation, progression, and therapy resistance on millions of cells from human tumors. Here we describe flow cytometry techniques that enable a "single-cell " view of cancer. High-dimensional techniques like mass cytometry enable multiplexed single-cell analysis of cell identity, clinical biomarkers, signaling network phospho-proteins, transcription factors, and functional readouts of proliferation, cell cycle status, and apoptosis. This capability pairs well with a signaling profiles approach that dissects mechanism by systematically perturbing and measuring many nodes in a signaling network. Single-cell approaches enable study of cellular heterogeneity of primary tissues and turn cell subsets into experimental controls or opportunities for new discovery. Rare populations of stem cells or therapy-resistant cancer cells can be identified and compared to other types of cells within the same sample. In the long term, these techniques will enable tracking of minimal residual disease (MRD) and disease progression. By better understanding biological systems that control development and cell-cell interactions in healthy and diseased contexts, we can learn to program cells to become therapeutic agents or target malignant signaling events to specifically kill cancer cells. Single-cell approaches that provide deep insight into cell signaling and fate decisions will be critical to optimizing the next generation of cancer treatments combining targeted approaches and immunotherapy.

  17. Multidisciplinary approaches to understanding collective cell migration in developmental biology.

    Science.gov (United States)

    Schumacher, Linus J; Kulesa, Paul M; McLennan, Rebecca; Baker, Ruth E; Maini, Philip K

    2016-06-01

    Mathematical models are becoming increasingly integrated with experimental efforts in the study of biological systems. Collective cell migration in developmental biology is a particularly fruitful application area for the development of theoretical models to predict the behaviour of complex multicellular systems with many interacting parts. In this context, mathematical models provide a tool to assess the consistency of experimental observations with testable mechanistic hypotheses. In this review, we showcase examples from recent years of multidisciplinary investigations of neural crest cell migration. The neural crest model system has been used to study how collective migration of cell populations is shaped by cell-cell interactions, cell-environmental interactions and heterogeneity between cells. The wide range of emergent behaviours exhibited by neural crest cells in different embryonal locations and in different organisms helps us chart out the spectrum of collective cell migration. At the same time, this diversity in migratory characteristics highlights the need to reconcile or unify the array of currently hypothesized mechanisms through the next generation of experimental data and generalized theoretical descriptions. © 2016 The Authors.

  18. The biologic effects of cigarette smoke on cancer cells.

    Science.gov (United States)

    Sobus, Samantha L; Warren, Graham W

    2014-12-01

    Smoking is one of the largest preventable risk factors for developing cancer, and continued smoking by cancer patients is associated with increased toxicity, recurrence, risk of second primary cancer, and mortality. Cigarette smoke (CS) contains thousands of chemicals, including many known carcinogens. The carcinogenic effects of CS are well established, but relatively little work has been done to evaluate the effects of CS on cancer cells. In this review of the literature, the authors demonstrate that CS induces a more malignant tumor phenotype by increasing proliferation, migration, invasion, and angiogenesis and by activating prosurvival cellular pathways. Significant work is needed to understand the biologic effect of CS on cancer biology, including the development of model systems and the identification of critical biologic mediators of CS-induced changes in cancer cell physiology. © 2014 American Cancer Society.

  19. Special Issue: International Congress of Cell Biology 2016, Prague

    Czech Academy of Sciences Publication Activity Database

    Stick, R.; Dráber, Pavel

    2017-01-01

    Roč. 254, č. 3 (2017), s. 1141-1142 ISSN 0033-183X R&D Projects: GA ČR GA16-25159S Institutional support: RVO:68378050 Keywords : cellular structures and functions, ,, , * tubulin isotypes * actin * transcription regulation * signaling pathways Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Cell biology Impact factor: 2.870, year: 2016

  20. Synthetic biology in cell-based cancer immunotherapy.

    Science.gov (United States)

    Chakravarti, Deboki; Wong, Wilson W

    2015-08-01

    The adoptive transfer of genetically engineered T cells with cancer-targeting receptors has shown tremendous promise for eradicating tumors in clinical trials. This form of cellular immunotherapy presents a unique opportunity to incorporate advanced systems and synthetic biology approaches to create cancer therapeutics with novel functions. We first review the development of synthetic receptors, switches, and circuits to control the location, duration, and strength of T cell activity against tumors. In addition, we discuss the cellular engineering and genome editing of host cells (or the chassis) to improve the efficacy of cell-based cancer therapeutics, and to reduce the time and cost of manufacturing. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Tumor necrosis factor (TNF) biology and cell death.

    Science.gov (United States)

    Bertazza, Loris; Mocellin, Simone

    2008-01-01

    Tumor necrosis factor (TNF) was the first cytokine to be used in humans for cancer therapy. However, its role in the treatment of cancer patients is debated. Most uncertainties in this field stem from the knowledge that the pathways directly activated or indirectly affected upon TNF engagement with its receptors can ultimately lead to very different outcomes in terms of cell survival. In this article, we summarize the fundamental molecular biology aspects of this cytokine. Such a basis is a prerequisite to critically approach the sometimes conflicting preclinical and clinical findings regarding the relationship between TNF, tumor biology and anticancer therapy. Although the last decade has witnessed remarkable advances in this field, we still do not know in detail how cells choose between life and death after TNF stimulation. Understanding this mechanism will not only shed new light on the physiological significance of TNF-driven programmed cell death but also help investigators maximize the anticancer potential of this cytokine.

  2. Unleashing the potential of the root hair cell as a single plant cell type model in root systems biology

    Directory of Open Access Journals (Sweden)

    Zhenzhen eQiao

    2013-11-01

    Full Text Available Plant root is an organ composed of multiple cell types with different functions. This multicellular complexity limits our understanding of root biology because –omics studies performed at the level of the entire root reflect the average responses of all cells composing the organ. To overcome this difficulty and allow a more comprehensive understanding of root cell biology, an approach is needed that would focus on one single cell type in the plant root. Because of its biological functions (i.e. uptake of water and various nutrients; primary site of infection by nitrogen-fixing bacteria in legumes, the root hair cell is an attractive single cell model to study root cell response to various stresses and treatments. To fully study their biology, we have recently optimized procedures in obtaining root hair cell samples. We culture the plants using an ultrasound aeroponic system maximizing root hair cell density on the entire root systems and allowing the homogeneous treatment of the root system. We then isolate the root hair cells in liquid nitrogen. Isolated root hair yields could be up to 800 to 1000 mg of plant cells from 60 root systems. Using soybean as a model, the purity of the root hair was assessed by comparing the expression level of genes previously identified as soybean root hair specific between preparations of isolated root hair cells and stripped roots, roots devoid in root hairs. Enlarging our tests to include other plant species, our results support the isolation of large quantities of highly purified root hair cells which is compatible with a systems biology approach.

  3. Agent-based modelling in synthetic biology.

    Science.gov (United States)

    Gorochowski, Thomas E

    2016-11-30

    Biological systems exhibit complex behaviours that emerge at many different levels of organization. These span the regulation of gene expression within single cells to the use of quorum sensing to co-ordinate the action of entire bacterial colonies. Synthetic biology aims to make the engineering of biology easier, offering an opportunity to control natural systems and develop new synthetic systems with useful prescribed behaviours. However, in many cases, it is not understood how individual cells should be programmed to ensure the emergence of a required collective behaviour. Agent-based modelling aims to tackle this problem, offering a framework in which to simulate such systems and explore cellular design rules. In this article, I review the use of agent-based models in synthetic biology, outline the available computational tools, and provide details on recently engineered biological systems that are amenable to this approach. I further highlight the challenges facing this methodology and some of the potential future directions. © 2016 The Author(s).

  4. Heavy ion induced DNA transfer in biological cells

    International Nuclear Information System (INIS)

    Vilaithong, T.; Yu, L.D.; Apavatjrut, P.; Phanchaisri, B.; Sangyuenyongpipat, S.; Anuntalabhochai, S.; Brown, I.G.

    2004-01-01

    Low-energy ion beam bombardment of biological materials for genetic modification purposes has experienced rapid growth in the last decade, particularly for the direct DNA transfer into living organisms including both plants and bacteria. Attempts have been made to understand the mechanisms involved in ion-bombardment-induced direct gene transfer into biological cells. Here we summarize the present status of the application of low-energy ions for genetic modification of living sample materials

  5. In Silico Dynamics: computer simulation in a Virtual Embryo ...

    Science.gov (United States)

    Abstract: Utilizing cell biological information to predict higher order biological processes is a significant challenge in predictive toxicology. This is especially true for highly dynamical systems such as the embryo where morphogenesis, growth and differentiation require precisely orchestrated interactions between diverse cell populations. In patterning the embryo, genetic signals setup spatial information that cells then translate into a coordinated biological response. This can be modeled as ‘biowiring diagrams’ representing genetic signals and responses. Because the hallmark of multicellular organization resides in the ability of cells to interact with one another via well-conserved signaling pathways, multiscale computational (in silico) models that enable these interactions provide a platform to translate cellular-molecular lesions perturbations into higher order predictions. Just as ‘the Cell’ is the fundamental unit of biology so too should it be the computational unit (‘Agent’) for modeling embryogenesis. As such, we constructed multicellular agent-based models (ABM) with ‘CompuCell3D’ (www.compucell3d.org) to simulate kinematics of complex cell signaling networks and enable critical tissue events for use in predictive toxicology. Seeding the ABMs with HTS/HCS data from ToxCast demonstrated the potential to predict, quantitatively, the higher order impacts of chemical disruption at the cellular or biochemical level. This is demonstrate

  6. Micro and nano-platforms for biological cell analysis

    DEFF Research Database (Denmark)

    Svendsen, Winnie Edith; Castillo, Jaime; Moresco, Jacob Lange

    2011-01-01

    In this paper some technological platforms developed for biological cell analysis will be presented and compared to existing systems. In brief, we present a novel micro cell culture chamber based on diffusion feeding of cells, into which cells can be introduced and extracted after culturing using...... from the cells, while passive modifications involve the presence of a peptide nanotube based scaffold for the cell culturing that mimics the in vivo environment. Two applications involving fluorescent in situ hybridization (FISH) analysis and cancer cell sorting are presented, as examples of further...... analysis that can be done after cell culturing. A platform able to automate the entire process from cell culturing to cell analysis by means of simple plug and play of various self-contained, individually fabricated modules is finally described....

  7. Discovering biological progression underlying microarray samples.

    Directory of Open Access Journals (Sweden)

    Peng Qiu

    2011-04-01

    Full Text Available In biological systems that undergo processes such as differentiation, a clear concept of progression exists. We present a novel computational approach, called Sample Progression Discovery (SPD, to discover patterns of biological progression underlying microarray gene expression data. SPD assumes that individual samples of a microarray dataset are related by an unknown biological process (i.e., differentiation, development, cell cycle, disease progression, and that each sample represents one unknown point along the progression of that process. SPD aims to organize the samples in a manner that reveals the underlying progression and to simultaneously identify subsets of genes that are responsible for that progression. We demonstrate the performance of SPD on a variety of microarray datasets that were generated by sampling a biological process at different points along its progression, without providing SPD any information of the underlying process. When applied to a cell cycle time series microarray dataset, SPD was not provided any prior knowledge of samples' time order or of which genes are cell-cycle regulated, yet SPD recovered the correct time order and identified many genes that have been associated with the cell cycle. When applied to B-cell differentiation data, SPD recovered the correct order of stages of normal B-cell differentiation and the linkage between preB-ALL tumor cells with their cell origin preB. When applied to mouse embryonic stem cell differentiation data, SPD uncovered a landscape of ESC differentiation into various lineages and genes that represent both generic and lineage specific processes. When applied to a prostate cancer microarray dataset, SPD identified gene modules that reflect a progression consistent with disease stages. SPD may be best viewed as a novel tool for synthesizing biological hypotheses because it provides a likely biological progression underlying a microarray dataset and, perhaps more importantly, the

  8. An interdepartmental Ph.D. program in computational biology and bioinformatics: the Yale perspective.

    Science.gov (United States)

    Gerstein, Mark; Greenbaum, Dov; Cheung, Kei; Miller, Perry L

    2007-02-01

    Computational biology and bioinformatics (CBB), the terms often used interchangeably, represent a rapidly evolving biological discipline. With the clear potential for discovery and innovation, and the need to deal with the deluge of biological data, many academic institutions are committing significant resources to develop CBB research and training programs. Yale formally established an interdepartmental Ph.D. program in CBB in May 2003. This paper describes Yale's program, discussing the scope of the field, the program's goals and curriculum, as well as a number of issues that arose in implementing the program. (Further updated information is available from the program's website, www.cbb.yale.edu.)

  9. Large Scale Computing and Storage Requirements for Biological and Environmental Research

    Energy Technology Data Exchange (ETDEWEB)

    DOE Office of Science, Biological and Environmental Research Program Office (BER),

    2009-09-30

    In May 2009, NERSC, DOE's Office of Advanced Scientific Computing Research (ASCR), and DOE's Office of Biological and Environmental Research (BER) held a workshop to characterize HPC requirements for BER-funded research over the subsequent three to five years. The workshop revealed several key points, in addition to achieving its goal of collecting and characterizing computing requirements. Chief among them: scientific progress in BER-funded research is limited by current allocations of computational resources. Additionally, growth in mission-critical computing -- combined with new requirements for collaborative data manipulation and analysis -- will demand ever increasing computing, storage, network, visualization, reliability and service richness from NERSC. This report expands upon these key points and adds others. It also presents a number of"case studies" as significant representative samples of the needs of science teams within BER. Workshop participants were asked to codify their requirements in this"case study" format, summarizing their science goals, methods of solution, current and 3-5 year computing requirements, and special software and support needs. Participants were also asked to describe their strategy for computing in the highly parallel,"multi-core" environment that is expected to dominate HPC architectures over the next few years.

  10. Using Femtosecond Laser Subcellular Surgery as a Tool to Study Cell Biology

    Energy Technology Data Exchange (ETDEWEB)

    Shen, N; Colvin, M E; Huser, T

    2007-02-27

    Research on cellular function and regulation would be greatly advanced by new instrumentation using methods to alter cellular processes with spatial discrimination on the nanometer-scale. We present a novel technique for targeting submicrometer sized organelles or other biologically important regions in living cells using femtosecond laser pulses. By tightly focusing these pulses beneath the cell membrane, we can vaporize cellular material inside the cell through nonlinear optical processes. This technique enables non-invasive manipulation of the physical structure of a cell with sub-micrometer resolution. We propose to study the role mitochondria play in cell proliferation and apoptosis. Our technique provides a unique tool for the study of cell biology.

  11. Derivation and computation of discrete-delay and continuous-delay SDEs in mathematical biology.

    Science.gov (United States)

    Allen, Edward J

    2014-06-01

    Stochastic versions of several discrete-delay and continuous-delay differential equations, useful in mathematical biology, are derived from basic principles carefully taking into account the demographic, environmental, or physiological randomness in the dynamic processes. In particular, stochastic delay differential equation (SDDE) models are derived and studied for Nicholson's blowflies equation, Hutchinson's equation, an SIS epidemic model with delay, bacteria/phage dynamics, and glucose/insulin levels. Computational methods for approximating the SDDE models are described. Comparisons between computational solutions of the SDDEs and independently formulated Monte Carlo calculations support the accuracy of the derivations and of the computational methods.

  12. Biological Dynamics Markup Language (BDML): an open format for representing quantitative biological dynamics data.

    Science.gov (United States)

    Kyoda, Koji; Tohsato, Yukako; Ho, Kenneth H L; Onami, Shuichi

    2015-04-01

    Recent progress in live-cell imaging and modeling techniques has resulted in generation of a large amount of quantitative data (from experimental measurements and computer simulations) on spatiotemporal dynamics of biological objects such as molecules, cells and organisms. Although many research groups have independently dedicated their efforts to developing software tools for visualizing and analyzing these data, these tools are often not compatible with each other because of different data formats. We developed an open unified format, Biological Dynamics Markup Language (BDML; current version: 0.2), which provides a basic framework for representing quantitative biological dynamics data for objects ranging from molecules to cells to organisms. BDML is based on Extensible Markup Language (XML). Its advantages are machine and human readability and extensibility. BDML will improve the efficiency of development and evaluation of software tools for data visualization and analysis. A specification and a schema file for BDML are freely available online at http://ssbd.qbic.riken.jp/bdml/. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

  13. Delivering The Benefits of Chemical-Biological Integration in Computational Toxicology at the EPA (ACS Fall meeting)

    Science.gov (United States)

    Abstract: Researchers at the EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The intent...

  14. Clinical relevance and biology of circulating tumor cells

    Science.gov (United States)

    2011-01-01

    Most breast cancer patients die due to metastases, and the early onset of this multistep process is usually missed by current tumor staging modalities. Therefore, ultrasensitive techniques have been developed to enable the enrichment, detection, isolation and characterization of disseminated tumor cells in bone marrow and circulating tumor cells in the peripheral blood of cancer patients. There is increasing evidence that the presence of these cells is associated with an unfavorable prognosis related to metastatic progression in the bone and other organs. This review focuses on investigations regarding the biology and clinical relevance of circulating tumor cells in breast cancer. PMID:22114869

  15. Graphene liquid cells for multi-technique analysis of biological cells in water environment

    Science.gov (United States)

    Matruglio, A.; Zucchiatti, P.; Birarda, G.; Marmiroli, B.; D'Amico, F.; Kocabas, C.; Kiskinova, M.; Vaccari, L.

    2018-05-01

    In-cell exploration of biomolecular constituents is the new frontier of cellular biology that will allow full access to structure-activity correlation of biomolecules, overcoming the limitations imposed by dissecting the cellular milieu. However, the presence of water, which is a very strong IR absorber and incompatible with the vacuum working conditions of all analytical methods using soft x-rays and electrons, poses severe constraint to perform important imaging and spectroscopic analyses under physiological conditions. Recent advances to separate the sample compartment in liquid cell are based on electron and photon transparent but molecular-impermeable graphene membranes. This strategy has opened a unique opportunity to explore technological materials under realistic operation conditions using various types of electron microscopy. However, the widespread of the graphene liquid cell applications is still impeded by the lack of well-established approaches for their massive production. We report on the first preliminary results for the fabrication of reproducible graphene liquid cells appropriate for the analysis of biological specimens in their natural hydrated environment with several crucial analytical techniques, namely FTIR microscopy, Raman spectroscopy, AFM, SEM and TEM.

  16. Computational cell model based on autonomous cell movement regulated by cell-cell signalling successfully recapitulates the "inside and outside" pattern of cell sorting

    Directory of Open Access Journals (Sweden)

    Ajioka Itsuki

    2007-09-01

    Full Text Available Abstract Background Development of multicellular organisms proceeds from a single fertilized egg as the combined effect of countless numbers of cellular interactions among highly dynamic cells. Since at least a reminiscent pattern of morphogenesis can be recapitulated in a reproducible manner in reaggregation cultures of dissociated embryonic cells, which is known as cell sorting, the cells themselves must possess some autonomous cell behaviors that assure specific and reproducible self-organization. Understanding of this self-organized dynamics of heterogeneous cell population seems to require some novel approaches so that the approaches bridge a gap between molecular events and morphogenesis in developmental and cell biology. A conceptual cell model in a computer may answer that purpose. We constructed a dynamical cell model based on autonomous cell behaviors, including cell shape, growth, division, adhesion, transformation, and motility as well as cell-cell signaling. The model gives some insights about what cellular behaviors make an appropriate global pattern of the cell population. Results We applied the model to "inside and outside" pattern of cell-sorting, in which two different embryonic cell types within a randomly mixed aggregate are sorted so that one cell type tends to gather in the central region of the aggregate and the other cell type surrounds the first cell type. Our model can modify the above cell behaviors by varying parameters related to them. We explored various parameter sets with which the "inside and outside" pattern could be achieved. The simulation results suggested that direction of cell movement responding to its neighborhood and the cell's mobility are important for this specific rearrangement. Conclusion We constructed an in silico cell model that mimics autonomous cell behaviors and applied it to cell sorting, which is a simple and appropriate phenomenon exhibiting self-organization of cell population. The model

  17. Toward synthesizing executable models in biology.

    Science.gov (United States)

    Fisher, Jasmin; Piterman, Nir; Bodik, Rastislav

    2014-01-01

    Over the last decade, executable models of biological behaviors have repeatedly provided new scientific discoveries, uncovered novel insights, and directed new experimental avenues. These models are computer programs whose execution mechanistically simulates aspects of the cell's behaviors. If the observed behavior of the program agrees with the observed biological behavior, then the program explains the phenomena. This approach has proven beneficial for gaining new biological insights and directing new experimental avenues. One advantage of this approach is that techniques for analysis of computer programs can be applied to the analysis of executable models. For example, one can confirm that a model agrees with experiments for all possible executions of the model (corresponding to all environmental conditions), even if there are a huge number of executions. Various formal methods have been adapted for this context, for example, model checking or symbolic analysis of state spaces. To avoid manual construction of executable models, one can apply synthesis, a method to produce programs automatically from high-level specifications. In the context of biological modeling, synthesis would correspond to extracting executable models from experimental data. We survey recent results about the usage of the techniques underlying synthesis of computer programs for the inference of biological models from experimental data. We describe synthesis of biological models from curated mutation experiment data, inferring network connectivity models from phosphoproteomic data, and synthesis of Boolean networks from gene expression data. While much work has been done on automated analysis of similar datasets using machine learning and artificial intelligence, using synthesis techniques provides new opportunities such as efficient computation of disambiguating experiments, as well as the ability to produce different kinds of models automatically from biological data.

  18. SIRT6 knockout cells resist apoptosis initiation but not progression: a computational method to evaluate the progression of apoptosis.

    Science.gov (United States)

    Domanskyi, Sergii; Nicholatos, Justin W; Schilling, Joshua E; Privman, Vladimir; Libert, Sergiy

    2017-11-01

    Apoptosis is essential for numerous processes, such as development, resistance to infections, and suppression of tumorigenesis. Here, we investigate the influence of the nutrient sensing and longevity-assuring enzyme SIRT6 on the dynamics of apoptosis triggered by serum starvation. Specifically, we characterize the progression of apoptosis in wild type and SIRT6 deficient mouse embryonic fibroblasts using time-lapse flow cytometry and computational modelling based on rate-equations and cell distribution analysis. We find that SIRT6 deficient cells resist apoptosis by delaying its initiation. Interestingly, once apoptosis is initiated, the rate of its progression is higher in SIRT6 null cells compared to identically cultured wild type cells. However, SIRT6 null cells succumb to apoptosis more slowly, not only in response to nutrient deprivation but also in response to other stresses. Our data suggest that SIRT6 plays a role in several distinct steps of apoptosis. Overall, we demonstrate the utility of our computational model to describe stages of apoptosis progression and the integrity of the cellular membrane. Such measurements will be useful in a broad range of biological applications.

  19. Cell biology, biophysics, and mechanobiology: From the basics to Clinics.

    Science.gov (United States)

    Zeng, Y

    2017-04-29

    Cell biology, biomechanics and biophysics are the key subjects that guide our understanding in diverse areas of tissue growth, development, remodeling and homeostasis. Novel discoveries such as molecular mechanism, and mechanobiological mechanism in cell biology, biomechanics and biophysics play essential roles in our understanding of the pathogenesis of various human diseases, as well as in designing the treatment of these diseases. In addition, studies in these areas will also facilitate early diagnostics of human diseases, such as cardiovascular diseases and cancer. In this special issue, we collected 10 original research articles and 1 review...

  20. [The implementation of computer model in research of dynamics of proliferation of cells of thyroid gland follicle].

    Science.gov (United States)

    Abduvaliev, A A; Gil'dieva, M S; Khidirov, B N; Saĭdalieva, M; Khasanov, A A; Musaeva, Sh N; Saatov, T S

    2012-04-01

    The article deals with the results of computational experiments in research of dynamics of proliferation of cells of thyroid gland follicle in normal condition and in the case of malignant neoplasm. The model studies demonstrated that the chronic increase of parameter of proliferation of cells of thyroid gland follicle results in abnormal behavior of numbers of cell cenosis of thyroid gland follicle. The stationary state interrupts, the auto-oscillations occur with transition to irregular oscillations with unpredictable cell proliferation and further to the "black hole" effect. It is demonstrated that the present medical biologic experimental data and theory propositions concerning the structural functional organization of thyroid gland on cell level permit to develop mathematical models for quantitative analysis of numbers of cell cenosis of thyroid gland follicle in normal conditions. The technique of modeling of regulative mechanisms of living systems and equations of cell cenosis regulations was used

  1. Physical properties of biological entities: an introduction to the ontology of physics for biology.

    Directory of Open Access Journals (Sweden)

    Daniel L Cook

    Full Text Available As biomedical investigators strive to integrate data and analyses across spatiotemporal scales and biomedical domains, they have recognized the benefits of formalizing languages and terminologies via computational ontologies. Although ontologies for biological entities-molecules, cells, organs-are well-established, there are no principled ontologies of physical properties-energies, volumes, flow rates-of those entities. In this paper, we introduce the Ontology of Physics for Biology (OPB, a reference ontology of classical physics designed for annotating biophysical content of growing repositories of biomedical datasets and analytical models. The OPB's semantic framework, traceable to James Clerk Maxwell, encompasses modern theories of system dynamics and thermodynamics, and is implemented as a computational ontology that references available upper ontologies. In this paper we focus on the OPB classes that are designed for annotating physical properties encoded in biomedical datasets and computational models, and we discuss how the OPB framework will facilitate biomedical knowledge integration.

  2. Physical properties of biological entities: an introduction to the ontology of physics for biology.

    Science.gov (United States)

    Cook, Daniel L; Bookstein, Fred L; Gennari, John H

    2011-01-01

    As biomedical investigators strive to integrate data and analyses across spatiotemporal scales and biomedical domains, they have recognized the benefits of formalizing languages and terminologies via computational ontologies. Although ontologies for biological entities-molecules, cells, organs-are well-established, there are no principled ontologies of physical properties-energies, volumes, flow rates-of those entities. In this paper, we introduce the Ontology of Physics for Biology (OPB), a reference ontology of classical physics designed for annotating biophysical content of growing repositories of biomedical datasets and analytical models. The OPB's semantic framework, traceable to James Clerk Maxwell, encompasses modern theories of system dynamics and thermodynamics, and is implemented as a computational ontology that references available upper ontologies. In this paper we focus on the OPB classes that are designed for annotating physical properties encoded in biomedical datasets and computational models, and we discuss how the OPB framework will facilitate biomedical knowledge integration. © 2011 Cook et al.

  3. The Histochemistry and Cell Biology omnium-gatherum: the year 2015 in review.

    Science.gov (United States)

    Taatjes, Douglas J; Roth, Jürgen

    2016-03-01

    We provide here our annual review/synopsis of all of the articles published in Histochemistry and Cell Biology (HCB) for the preceding year. In 2015, HCB published 102 articles, representing a wide variety of topics and methodologies. For ease of access to these differing topics, we have created categories, as determined by the types of articles presented to provide a quick index representing the general areas covered. This year, these categories include: (1) advances in methodologies; (2) molecules in health and disease; (3) organelles, subcellular structures, and compartments; (4) the nucleus; (5) stem cells and tissue engineering; (6) cell cultures: properties and capabilities; (7) connective tissues and extracellular matrix; (8) developmental biology; (9) nervous system; (10) musculoskeletal system; (11) respiratory and cardiovascular system; (12) liver and gastrointestinal tract; and (13) male and female reproductive systems. Of note, the categories proceed from methods development, to molecules, intracellular compartments, stem cells and cell culture, extracellular matrix, developmental biology, and finishing with various organ systems, hopefully presenting a logical journey from methods to organismal molecules, cells, and whole tissue systems.

  4. 100 years after Smoluchowski: stochastic processes in cell biology

    International Nuclear Information System (INIS)

    Holcman, D; Schuss, Z

    2017-01-01

    100 years after Smoluchowski introduced his approach to stochastic processes, they are now at the basis of mathematical and physical modeling in cellular biology: they are used for example to analyse and to extract features from a large number (tens of thousands) of single molecular trajectories or to study the diffusive motion of molecules, proteins or receptors. Stochastic modeling is a new step in large data analysis that serves extracting cell biology concepts. We review here Smoluchowski’s approach to stochastic processes and provide several applications for coarse-graining diffusion, studying polymer models for understanding nuclear organization and finally, we discuss the stochastic jump dynamics of telomeres across cell division and stochastic gene regulation. (topical review)

  5. Unravelling biology and shifting paradigms in cancer with single-cell sequencing.

    Science.gov (United States)

    Baslan, Timour; Hicks, James

    2017-08-24

    The fundamental operative unit of a cancer is the genetically and epigenetically innovative single cell. Whether proliferating or quiescent, in the primary tumour mass or disseminated elsewhere, single cells govern the parameters that dictate all facets of the biology of cancer. Thus, single-cell analyses provide the ultimate level of resolution in our quest for a fundamental understanding of this disease. Historically, this quest has been hampered by technological shortcomings. In this Opinion article, we argue that the rapidly evolving field of single-cell sequencing has unshackled the cancer research community of these shortcomings. From furthering an elemental understanding of intra-tumoural genetic heterogeneity and cancer genome evolution to illuminating the governing principles of disease relapse and metastasis, we posit that single-cell sequencing promises to unravel the biology of all facets of this disease.

  6. Applied Developmental Biology: Making Human Pancreatic Beta Cells for Diabetics.

    Science.gov (United States)

    Melton, Douglas A

    2016-01-01

    Understanding the genes and signaling pathways that determine the differentiation and fate of a cell is a central goal of developmental biology. Using that information to gain mastery over the fates of cells presents new approaches to cell transplantation and drug discovery for human diseases including diabetes. © 2016 Elsevier Inc. All rights reserved.

  7. Crosstalk between stromal cells and cancer cells in pancreatic cancer: New insights into stromal biology.

    Science.gov (United States)

    Zhan, Han-Xiang; Zhou, Bin; Cheng, Yu-Gang; Xu, Jian-Wei; Wang, Lei; Zhang, Guang-Yong; Hu, San-Yuan

    2017-04-28

    Pancreatic cancer (PC) remains one of the most lethal malignancies worldwide. Increasing evidence has confirmed the pivotal role of stromal components in the regulation of carcinogenesis, invasion, metastasis, and therapeutic resistance in PC. Interaction between neoplastic cells and stromal cells builds a specific microenvironment, which further modulates the malignant properties of cancer cells. Instead of being a "passive bystander", stroma may play a role as a "partner in crime" in PC. However, the role of stromal components in PC is complex and requires further investigation. In this article, we review recent advances regarding the regulatory roles and mechanisms of stroma biology, especially the cellular components such as pancreatic stellate cells, macrophages, neutrophils, adipocytes, epithelial cells, pericytes, mast cells, and lymphocytes, in PC. Crosstalk between stromal cells and cancer cells is thoroughly investigated. We also review the prognostic value and molecular therapeutic targets of stroma in PC. This review may help us further understand the molecular mechanisms of stromal biology and its role in PC development and therapeutic resistance. Moreover, targeting stroma components may provide new therapeutic strategies for this stubborn disease. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Proteomics in studying cancer stem cell biology.

    Science.gov (United States)

    Kranenburg, Onno; Emmink, Benjamin L; Knol, Jaco; van Houdt, Winan J; Rinkes, Inne H M Borel; Jimenez, Connie R

    2012-06-01

    Normal multipotent tissue stem cells (SCs) are the driving force behind tissue turnover and repair. The cancer stem cell theory holds that tumors also contain stem-like cells that drive tumor growth and metastasis formation. However, very little is known about the regulation of SC maintenance pathways in cancer and how these are affected by cancer-specific genetic alterations and by treatment. Proteomics is emerging as a powerful tool to identify the signaling complexes and pathways that control multi- and pluri-potency and SC differentiation. Here, the authors review the novel insights that these studies have provided and present a comprehensive strategy for the use of proteomics in studying cancer SC biology.

  9. After the Greeting: Realizing the Potential of Physical Models in Cell Biology.

    Science.gov (United States)

    Paluch, Ewa K

    2015-12-01

    Biophysics is increasingly taking center stage in cell biology as the tools for precise quantifications of cellular behaviors expand. Interdisciplinary approaches, combining quantitative physical modeling with cell biology, are of growing interest to journal editors, funding agencies, and hiring committees. However, despite an ever-increasing emphasis on the importance of interdisciplinary research, the student trained in biology may still be at a loss as to what it actually means. I discuss here some considerations on how to achieve meaningful and high-quality interdisciplinary work. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. In search of mitochondrial mechanisms: interfield excursions between cell biology and biochemistry.

    Science.gov (United States)

    Bechtel, William; Abrahamsen, Adele

    2007-01-01

    Developing models of biological mechanisms, such as those involved in respiration in cells, often requires collaborative effort drawing upon techniques developed and information generated in different disciplines. Biochemists in the early decades of the 20th century uncovered all but the most elusive chemical operations involved in cellular respiration, but were unable to align the reaction pathways with particular structures in the cell. During the period 1940-1965 cell biology was emerging as a new discipline and made distinctive contributions to understanding the role of the mitochondrion and its component parts in cellular respiration. In particular, by developing techniques for localizing enzymes or enzyme systems in specific cellular components, cell biologists provided crucial information about the organized structures in which the biochemical reactions occurred. Although the idea that biochemical operations are intimately related to and depend on cell structures was at odds with the then-dominant emphasis on systems of soluble enzymes in biochemistry, a reconceptualization of energetic processes in the 1960s and 1970s made it clear why cell structure was critical to the biochemical account. This paper examines how numerous excursions between biochemistry and cell biology contributed a new understanding of the mechanism of cellular respiration.

  11. Models to Study NK Cell Biology and Possible Clinical Application.

    Science.gov (United States)

    Zamora, Anthony E; Grossenbacher, Steven K; Aguilar, Ethan G; Murphy, William J

    2015-08-03

    Natural killer (NK) cells are large granular lymphocytes of the innate immune system, responsible for direct targeting and killing of both virally infected and transformed cells. NK cells rapidly recognize and respond to abnormal cells in the absence of prior sensitization due to their wide array of germline-encoded inhibitory and activating receptors, which differs from the receptor diversity found in B and T lymphocytes that is due to the use of recombination-activation gene (RAG) enzymes. Although NK cells have traditionally been described as natural killers that provide a first line of defense prior to the induction of adaptive immunity, a more complex view of NK cells is beginning to emerge, indicating they may also function in various immunoregulatory roles and have the capacity to shape adaptive immune responses. With the growing appreciation for the diverse functions of NK cells, and recent technological advancements that allow for a more in-depth understanding of NK cell biology, we can now begin to explore new ways to manipulate NK cells to increase their clinical utility. In this overview unit, we introduce the reader to various aspects of NK cell biology by reviewing topics ranging from NK cell diversity and function, mouse models, and the roles of NK cells in health and disease, to potential clinical applications. © 2015 by John Wiley & Sons, Inc. Copyright © 2015 John Wiley & Sons, Inc.

  12. Biological Influence of Deuterium on Procariotic and Eukaryotic Cells

    OpenAIRE

    Oleg Mosin; Ignat Ignatov

    2014-01-01

    Biologic influence of deuterium (D) on cells of various taxonomic groups of prokaryotic and eukaryotic microorganisms realizing methylotrophic, chemoheterotrophic, photo-organotrophic, and photosynthetic ways of assimilation of carbon substrates are investigated at growth on media with heavy water (D2О). The method of step by step adaptation technique of cells to D2О was developed, consisting in plating of cells on 2 % agarose nutrient media containing increasing gradient of concentration of ...

  13. Machine learning and computer vision approaches for phenotypic profiling.

    Science.gov (United States)

    Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J

    2017-01-02

    With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.

  14. Scale-free flow of life: on the biology, economics, and physics of the cell

    Directory of Open Access Journals (Sweden)

    Kurakin Alexei

    2009-05-01

    Full Text Available Abstract The present work is intended to demonstrate that most of the paradoxes, controversies, and contradictions accumulated in molecular and cell biology over many years of research can be readily resolved if the cell and living systems in general are re-interpreted within an alternative paradigm of biological organization that is based on the concepts and empirical laws of nonequilibrium thermodynamics. In addition to resolving paradoxes and controversies, the proposed re-conceptualization of the cell and biological organization reveals hitherto unappreciated connections among many seemingly disparate phenomena and observations, and provides new and powerful insights into the universal principles governing the emergence and organizational dynamics of living systems on each and every scale of biological organizational hierarchy, from proteins and cells to economies and ecologies.

  15. Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells

    Science.gov (United States)

    Korkut, Anil; Wang, Weiqing; Demir, Emek; Aksoy, Bülent Arman; Jing, Xiaohong; Molinelli, Evan J; Babur, Özgün; Bemis, Debra L; Onur Sumer, Selcuk; Solit, David B; Pratilas, Christine A; Sander, Chris

    2015-01-01

    Resistance to targeted cancer therapies is an important clinical problem. The discovery of anti-resistance drug combinations is challenging as resistance can arise by diverse escape mechanisms. To address this challenge, we improved and applied the experimental-computational perturbation biology method. Using statistical inference, we build network models from high-throughput measurements of molecular and phenotypic responses to combinatorial targeted perturbations. The models are computationally executed to predict the effects of thousands of untested perturbations. In RAF-inhibitor resistant melanoma cells, we measured 143 proteomic/phenotypic entities under 89 perturbation conditions and predicted c-Myc as an effective therapeutic co-target with BRAF or MEK. Experiments using the BET bromodomain inhibitor JQ1 affecting the level of c-Myc protein and protein kinase inhibitors targeting the ERK pathway confirmed the prediction. In conclusion, we propose an anti-cancer strategy of co-targeting a specific upstream alteration and a general downstream point of vulnerability to prevent or overcome resistance to targeted drugs. DOI: http://dx.doi.org/10.7554/eLife.04640.001 PMID:26284497

  16. Günter Blobel: Pioneer of molecular cell biology (1936-2018).

    Science.gov (United States)

    2018-04-02

    Günter Blobel was a scientific colossus who dedicated his career to understanding the mechanisms for protein sorting to membrane organelles. His monumental contributions established research paradigms for major arenas of molecular cell biology. For this work, he received many accolades, including the Nobel Prize in Medicine or Physiology in 1999. He was a scientist of extreme passion and a nurturing mentor for generations of researchers, imbuing them with his deep love of cell biology and galvanizing them to continue his scientific legacy. Günter passed away on February 18, 2018, at the age of 81. © 2018 Rockefeller University Press.

  17. Discovering local patterns of co - evolution: computational aspects and biological examples

    Directory of Open Access Journals (Sweden)

    Tuller Tamir

    2010-01-01

    Full Text Available Abstract Background Co-evolution is the process in which two (or more sets of orthologs exhibit a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn about the functional interdependencies between sets of genes and cellular functions and to predict physical interactions. More generally, it can be used for answering fundamental questions about the evolution of biological systems. Orthologs that exhibit a strong signal of co-evolution in a certain part of the evolutionary tree may show a mild signal of co-evolution in other branches of the tree. The major reasons for this phenomenon are noise in the biological input, genes that gain or lose functions, and the fact that some measures of co-evolution relate to rare events such as positive selection. Previous publications in the field dealt with the problem of finding sets of genes that co-evolved along an entire underlying phylogenetic tree, without considering the fact that often co-evolution is local. Results In this work, we describe a new set of biological problems that are related to finding patterns of local co-evolution. We discuss their computational complexity and design algorithms for solving them. These algorithms outperform other bi-clustering methods as they are designed specifically for solving the set of problems mentioned above. We use our approach to trace the co-evolution of fungal, eukaryotic, and mammalian genes at high resolution across the different parts of the corresponding phylogenetic trees. Specifically, we discover regions in the fungi tree that are enriched with positive evolution. We show that metabolic genes exhibit a remarkable level of co-evolution and different patterns of co-evolution in various biological datasets. In addition, we find that protein complexes that are related to gene expression exhibit non-homogenous levels of co-evolution across different parts of the fungi evolutionary line. In the case of mammalian evolution

  18. Evaluation of the Redesign of an Undergraduate Cell Biology Course

    Science.gov (United States)

    McEwen, Laura April; Harris, dik; Schmid, Richard F.; Vogel, Jackie; Western, Tamara; Harrison, Paul

    2009-01-01

    This article offers a case study of the evaluation of a redesigned and redeveloped laboratory-based cell biology course. The course was a compulsory element of the biology program, but the laboratory had become outdated and was inadequately equipped. With the support of a faculty-based teaching improvement project, the teaching team redesigned the…

  19. The Potential of the Cell Processor for Scientific Computing

    Energy Technology Data Exchange (ETDEWEB)

    Williams, Samuel; Shalf, John; Oliker, Leonid; Husbands, Parry; Kamil, Shoaib; Yelick, Katherine

    2005-10-14

    The slowing pace of commodity microprocessor performance improvements combined with ever-increasing chip power demands has become of utmost concern to computational scientists. As a result, the high performance computing community is examining alternative architectures that address the limitations of modern cache-based designs. In this work, we examine the potential of the using the forth coming STI Cell processor as a building block for future high-end computing systems. Our work contains several novel contributions. We are the first to present quantitative Cell performance data on scientific kernels and show direct comparisons against leading superscalar (AMD Opteron), VLIW (IntelItanium2), and vector (Cray X1) architectures. Since neither Cell hardware nor cycle-accurate simulators are currently publicly available, we develop both analytical models and simulators to predict kernel performance. Our work also explores the complexity of mapping several important scientific algorithms onto the Cells unique architecture. Additionally, we propose modest microarchitectural modifications that could significantly increase the efficiency of double-precision calculations. Overall results demonstrate the tremendous potential of the Cell architecture for scientific computations in terms of both raw performance and power efficiency.

  20. Effects of space environment on biological characteristics of melanoma B16 cells

    International Nuclear Information System (INIS)

    Geng Chuanying; Xiang Qing; Xu Mei; Li Hongyan; Xu Bo; Fang Qing; Tang Jingtian; Guo Yupeng

    2006-01-01

    Objective: To examine the effects of space environment on biological characteristics of melanoma B16 Cells. Methods: B16 cells were carried to the space (in orbit for 8 days, circle the earth 286 times) by the 20th Chinese recoverable satellite, and then harvested and monocloned. 110 strains of space B16 cells were obtained in total. Ten strains of space B16 cells were selected and its morphological changes were examined with the phasecontrast microscope. Flow cytometry and MTT assay were carried out to evaluate the cell cycle and cell viability. Results Morphological changes were observed in the space cells, and melainin granules on the surface in some cells. It was demonstrated by MTF assay that space cells viability varied muti- directionally. It was showed by flow cytometry analysis that G1 phase of space cells was prolonged, S phase shortened. Conclusion: Space environment may change the biological characteristics of melanoma B16 cells. (authors)

  1. Editorial Introduction [to Female Germ Cells: Biology and Genetic Risk

    Science.gov (United States)

    This is an editorial introduction to the special issue of utation Research, titled, emale Germ Cells: Biology and Genetic isk, which is an attempt to present a collection of papers that emphasize the distinct properties of female germ cells and their characteristic response to mu...

  2. The Emerging Role of PEDF in Stem Cell Biology

    Science.gov (United States)

    Elahy, Mina; Baindur-Hudson, Swati; Dass, Crispin R.

    2012-01-01

    Encoded by a single gene, PEDF is a 50 kDa glycoprotein that is highly conserved and is widely expressed among many tissues. Most secreted PEDF deposits within the extracellular matrix, with cell-type-specific functions. While traditionally PEDF is known as a strong antiangiogenic factor, more recently, as this paper highlights, PEDF has been linked with stem cell biology, and there is now accumulating evidence demonstrating the effects of PEDF in a variety of stem cells, mainly in supporting stem cell survival and maintaining multipotency. PMID:22675247

  3. Biology of lung cancer: genetic mutation, epithelial-mesenchymal transition, and cancer stem cells.

    Science.gov (United States)

    Aoi, Takashi

    2016-09-01

    At present, most cases of unresectable cancer cannot be cured. Genetic mutations, EMT, and cancer stem cells are three major issues linked to poor prognosis in such cases, all connected by inter- and intra-tumor heterogeneity. Issues on inter-/intra-tumor heterogeneity of genetic mutation could be resolved with recent and future technologies of deep sequencers, whereas, regarding such issues as the "same genome, different epigenome/phenotype", we expect to solve many of these problems in the future through further research in stem cell biology. We herein review and discuss the three major issues in the biology of cancers, especially from the standpoint of stem cell biology.

  4. Transcriptomic signatures shaped by cell proportions shed light on comparative developmental biology

    Czech Academy of Sciences Publication Activity Database

    Pantalacci, S.; Gueguen, L.; Petit, C.; Lambert, A.; Peterková, Renata; Sémon, E.

    2017-01-01

    Roč. 18, feb (2017), s. 29 ISSN 1474-760X R&D Projects: GA ČR(CZ) GB14-37368G Institutional support: RVO:68378041 Keywords : comparative transcriptomics * developmental biology * transcriptomic signature Subject RIV: EA - Cell Biology OBOR OECD: Developmental biology Impact factor: 11.908, year: 2016

  5. Computational Modeling in Tissue Engineering

    CERN Document Server

    2013-01-01

    One of the major challenges in tissue engineering is the translation of biological knowledge on complex cell and tissue behavior into a predictive and robust engineering process. Mastering this complexity is an essential step towards clinical applications of tissue engineering. This volume discusses computational modeling tools that allow studying the biological complexity in a more quantitative way. More specifically, computational tools can help in:  (i) quantifying and optimizing the tissue engineering product, e.g. by adapting scaffold design to optimize micro-environmental signals or by adapting selection criteria to improve homogeneity of the selected cell population; (ii) quantifying and optimizing the tissue engineering process, e.g. by adapting bioreactor design to improve quality and quantity of the final product; and (iii) assessing the influence of the in vivo environment on the behavior of the tissue engineering product, e.g. by investigating vascular ingrowth. The book presents examples of each...

  6. Theoretical discussion for quantum computation in biological systems

    Science.gov (United States)

    Baer, Wolfgang

    2010-04-01

    Analysis of the brain as a physical system, that has the capacity of generating a display of every day observed experiences and contains some knowledge of the physical reality which stimulates those experiences, suggests the brain executes a self-measurement process described by quantum theory. Assuming physical reality is a universe of interacting self-measurement loops, we present a model of space as a field of cells executing such self-measurement activities. Empty space is the observable associated with the measurement of this field when the mass and charge density defining the material aspect of the cells satisfy the least action principle. Content is the observable associated with the measurement of the quantum wave function ψ interpreted as mass-charge displacements. The illusion of space and its content incorporated into cognitive biological systems is evidence of self-measurement activity that can be associated with quantum operations.

  7. Cameo: A Python Library for Computer Aided Metabolic Engineering and Optimization of Cell Factories.

    Science.gov (United States)

    Cardoso, João G R; Jensen, Kristian; Lieven, Christian; Lærke Hansen, Anne Sofie; Galkina, Svetlana; Beber, Moritz; Özdemir, Emre; Herrgård, Markus J; Redestig, Henning; Sonnenschein, Nikolaus

    2018-04-20

    Computational systems biology methods enable rational design of cell factories on a genome-scale and thus accelerate the engineering of cells for the production of valuable chemicals and proteins. Unfortunately, the majority of these methods' implementations are either not published, rely on proprietary software, or do not provide documented interfaces, which has precluded their mainstream adoption in the field. In this work we present cameo, a platform-independent software that enables in silico design of cell factories and targets both experienced modelers as well as users new to the field. It is written in Python and implements state-of-the-art methods for enumerating and prioritizing knockout, knock-in, overexpression, and down-regulation strategies and combinations thereof. Cameo is an open source software project and is freely available under the Apache License 2.0. A dedicated Web site including documentation, examples, and installation instructions can be found at http://cameo.bio . Users can also give cameo a try at http://try.cameo.bio .

  8. A data integration approach for cell cycle analysis oriented to model simulation in systems biology

    Directory of Open Access Journals (Sweden)

    Mosca Ettore

    2007-08-01

    Full Text Available Abstract Background The cell cycle is one of the biological processes most frequently investigated in systems biology studies and it involves the knowledge of a large number of genes and networks of protein interactions. A deep knowledge of the molecular aspect of this biological process can contribute to making cancer research more accurate and innovative. In this context the mathematical modelling of the cell cycle has a relevant role to quantify the behaviour of each component of the systems. The mathematical modelling of a biological process such as the cell cycle allows a systemic description that helps to highlight some features such as emergent properties which could be hidden when the analysis is performed only from a reductionism point of view. Moreover, in modelling complex systems, a complete annotation of all the components is equally important to understand the interaction mechanism inside the network: for this reason data integration of the model components has high relevance in systems biology studies. Description In this work, we present a resource, the Cell Cycle Database, intended to support systems biology analysis on the Cell Cycle process, based on two organisms, yeast and mammalian. The database integrates information about genes and proteins involved in the cell cycle process, stores complete models of the interaction networks and allows the mathematical simulation over time of the quantitative behaviour of each component. To accomplish this task, we developed, a web interface for browsing information related to cell cycle genes, proteins and mathematical models. In this framework, we have implemented a pipeline which allows users to deal with the mathematical part of the models, in order to solve, using different variables, the ordinary differential equation systems that describe the biological process. Conclusion This integrated system is freely available in order to support systems biology research on the cell cycle and

  9. Flow velocity-driven differentiation of human mesenchymal stromal cells in silk fibroin scaffolds: A combined experimental and computational approach.

    Directory of Open Access Journals (Sweden)

    Jolanda Rita Vetsch

    Full Text Available Mechanical loading plays a major role in bone remodeling and fracture healing. Mimicking the concept of mechanical loading of bone has been widely studied in bone tissue engineering by perfusion cultures. Nevertheless, there is still debate regarding the in-vitro mechanical stimulation regime. This study aims at investigating the effect of two different flow rates (vlow = 0.001m/s and vhigh = 0.061m/s on the growth of mineralized tissue produced by human mesenchymal stromal cells cultured on 3-D silk fibroin scaffolds. The flow rates applied were chosen to mimic the mechanical environment during early fracture healing or during bone remodeling, respectively. Scaffolds cultured under static conditions served as a control. Time-lapsed micro-computed tomography showed that mineralized extracellular matrix formation was completely inhibited at vlow compared to vhigh and the static group. Biochemical assays and histology confirmed these results and showed enhanced osteogenic differentiation at vhigh whereas the amount of DNA was increased at vlow. The biological response at vlow might correspond to the early stage of fracture healing, where cell proliferation and matrix production is prominent. Visual mapping of shear stresses, simulated by computational fluid dynamics, to 3-D micro-computed tomography data revealed that shear stresses up to 0.39mPa induced a higher DNA amount and shear stresses between 0.55mPa and 24mPa induced osteogenic differentiation. This study demonstrates the feasibility to drive cell behavior of human mesenchymal stromal cells by the flow velocity applied in agreement with mechanical loading mimicking early fracture healing (vlow or bone remodeling (vhigh. These results can be used in the future to tightly control the behavior of human mesenchymal stromal cells towards proliferation or differentiation. Additionally, the combination of experiment and simulation presented is a strong tool to link biological responses to

  10. Computer Simulation and Data Analysis in Molecular Biology and Biophysics An Introduction Using R

    CERN Document Server

    Bloomfield, Victor

    2009-01-01

    This book provides an introduction, suitable for advanced undergraduates and beginning graduate students, to two important aspects of molecular biology and biophysics: computer simulation and data analysis. It introduces tools to enable readers to learn and use fundamental methods for constructing quantitative models of biological mechanisms, both deterministic and with some elements of randomness, including complex reaction equilibria and kinetics, population models, and regulation of metabolism and development; to understand how concepts of probability can help in explaining important features of DNA sequences; and to apply a useful set of statistical methods to analysis of experimental data from spectroscopic, genomic, and proteomic sources. These quantitative tools are implemented using the free, open source software program R. R provides an excellent environment for general numerical and statistical computing and graphics, with capabilities similar to Matlab®. Since R is increasingly used in bioinformat...

  11. Using synthetic biology to make cells tomorrow's test tubes.

    Science.gov (United States)

    Garcia, Hernan G; Brewster, Robert C; Phillips, Rob

    2016-04-18

    The main tenet of physical biology is that biological phenomena can be subject to the same quantitative and predictive understanding that physics has afforded in the context of inanimate matter. However, the inherent complexity of many of these biological processes often leads to the derivation of complex theoretical descriptions containing a plethora of unknown parameters. Such complex descriptions pose a conceptual challenge to the establishment of a solid basis for predictive biology. In this article, we present various exciting examples of how synthetic biology can be used to simplify biological systems and distill these phenomena down to their essential features as a means to enable their theoretical description. Here, synthetic biology goes beyond previous efforts to engineer nature and becomes a tool to bend nature to understand it. We discuss various recent and classic experiments featuring applications of this synthetic approach to the elucidation of problems ranging from bacteriophage infection, to transcriptional regulation in bacteria and in developing embryos, to evolution. In all of these examples, synthetic biology provides the opportunity to turn cells into the equivalent of a test tube, where biological phenomena can be reconstituted and our theoretical understanding put to test with the same ease that these same phenomena can be studied in the in vitro setting.

  12. Emerging concepts and future challenges in innate lymphoid cell biology

    Science.gov (United States)

    Artis, David

    2016-01-01

    Innate lymphoid cells (ILCs) are innate immune cells that are ubiquitously distributed in lymphoid and nonlymphoid tissues and enriched at mucosal and barrier surfaces. Three major ILC subsets are recognized in mice and humans. Each of these subsets interacts with innate and adaptive immune cells and integrates cues from the epithelium, the microbiota, and pathogens to regulate inflammation, immunity, tissue repair, and metabolic homeostasis. Although intense study has elucidated many aspects of ILC development, phenotype, and function, numerous challenges remain in the field of ILC biology. In particular, recent work has highlighted key new questions regarding how these cells communicate with their environment and other cell types during health and disease. This review summarizes new findings in this rapidly developing field that showcase the critical role ILCs play in directing immune responses through their ability to interact with a variety of hematopoietic and nonhematopoietic cells. In addition, we define remaining challenges and emerging questions facing the field. Finally, this review discusses the potential application of basic studies of ILC biology to the development of new treatments for human patients with inflammatory and infectious diseases in which ILCs play a role. PMID:27811053

  13. Dispensing processes impact apparent biological activity as determined by computational and statistical analyses.

    Directory of Open Access Journals (Sweden)

    Sean Ekins

    Full Text Available Dispensing and dilution processes may profoundly influence estimates of biological activity of compounds. Published data show Ephrin type-B receptor 4 IC50 values obtained via tip-based serial dilution and dispensing versus acoustic dispensing with direct dilution differ by orders of magnitude with no correlation or ranking of datasets. We generated computational 3D pharmacophores based on data derived by both acoustic and tip-based transfer. The computed pharmacophores differ significantly depending upon dispensing and dilution methods. The acoustic dispensing-derived pharmacophore correctly identified active compounds in a subsequent test set where the tip-based method failed. Data from acoustic dispensing generates a pharmacophore containing two hydrophobic features, one hydrogen bond donor and one hydrogen bond acceptor. This is consistent with X-ray crystallography studies of ligand-protein interactions and automatically generated pharmacophores derived from this structural data. In contrast, the tip-based data suggest a pharmacophore with two hydrogen bond acceptors, one hydrogen bond donor and no hydrophobic features. This pharmacophore is inconsistent with the X-ray crystallographic studies and automatically generated pharmacophores. In short, traditional dispensing processes are another important source of error in high-throughput screening that impacts computational and statistical analyses. These findings have far-reaching implications in biological research.

  14. Computer simulation of induced electric currents and fields in biological bodies by 60 Hz magnetic fields

    International Nuclear Information System (INIS)

    Xi Weiguo; Stuchly, M.A.; Gandhi, O.P.

    1993-01-01

    Possible health effects of human exposure to 60 Hz magnetic fields are a subject of increasing concern. An understanding of the coupling of electromagnetic fields to human body tissues is essential for assessment of their biological effects. A method is presented for the computerized simulation of induced electric currents and fields in bodies of men and rodents from power-line frequency magnetic fields. In the impedance method, the body is represented by a 3 dimensional impedance network. The computational model consists of several tens of thousands of cubic numerical cells and thus represented a realistic shape. The modelling for humans is performed with two models, a heterogeneous model based on cross-section anatomy and a homogeneous one using an average tissue conductivity. A summary of computed results of induced electric currents and fields is presented. It is confirmed that induced currents are lower than endangerous current levels for most environmental exposures. However, the induced current density varies greatly, with the maximum being at least 10 times larger than the average. This difference is likely to be greater when more detailed anatomy and morphology are considered. 15 refs., 2 figs., 1 tab

  15. In vitro assessment of a computer-designed potential anticancer agent in cervical cancer cells

    Directory of Open Access Journals (Sweden)

    Michelle Helen Visagie

    Full Text Available BACKGROUND: Computer-based technology is becoming increasingly essential in biological research where drug discovery programs start with the identification of suitable drug targets. 2-Methoxyestradiol (2ME2 is a 17ß-estradiol metabolite that induces apoptosis in various cancer cell lines including cervical cancer, breast cancer and multiple myeloma. Owing to 2ME2's poor in vivo bioavailability, our laboratory in silico-designed and subsequently synthesized a novel 2ME2 analogue, 2-ethyl-3-O-sulphamoyl-estra-1,3,5(10,15-tetraen-17-ol (ESE-15-ol, using receptor- and ligand molecular modeling. In this study, the biological effects of ESE-15-ol (180 nM and its parent molecule, 2ME2 (1 μM, were assessed on morphology and apoptosis induction in cervical cancer cells. RESULTS: Transmission electron microscopy, scanning electron microscopy and polarization-optical transmitted light differential interference contrast (PlasDIC images demonstrated morphological hallmarks of apoptosis including apoptotic bodies, shrunken cells, vacuoles, reduced cell density and cell debris. Flow cytometry analysis showed apoptosis induction by means of annexin V-FITC staining. Cell cycle analysis showed that ESE-15-ol exposure resulted in a statistically significant increase in the G2M phase (72% compared to 2ME2 (19%. Apoptosis induction was more pronounced when cells were exposed to ESE-15-ol compared to 2ME2. Spectrophotometric analysis of caspase 8 activity demonstrated that 2ME2 and ESE-15-ol both induced caspase 8 activation by 2- and 1.7-fold respectively indicating the induction of the apoptosis. However, ESE-15-ol exerted all of the above-mentioned effects at a much lower pharmacological concentration (180 nM compared to 2ME2 (1 μM physiological concentration. CONCLUSION: Computer-based technology is essential in drug discovery and together with in vitro studies for the evaluation of these in silico-designed compounds, drug development can be improved to be

  16. What it takes to understand and cure a living system: computational systems biology and a systems biology-driven pharmacokinetics-pharmacodynamics platform

    NARCIS (Netherlands)

    Swat, Maciej; Kiełbasa, Szymon M.; Polak, Sebastian; Olivier, Brett; Bruggeman, Frank J.; Tulloch, Mark Quinton; Snoep, Jacky L.; Verhoeven, Arthur J.; Westerhoff, Hans V.

    2011-01-01

    The utility of model repositories is discussed in the context of systems biology (SB). It is shown how such repositories, and in particular their live versions, can be used for computational SB: we calculate the robustness of the yeast glycolytic network with respect to perturbations of one of its

  17. SYSTEMS BIOLOGY AND METABOLIC ENGINEERING OF ARTHROSPIRA CELL FACTORIES

    Directory of Open Access Journals (Sweden)

    Amornpan Klanchui

    2012-10-01

    Full Text Available Arthrospira are attractive candidates to serve as cell factories for production of many valuable compounds useful for food, feed, fuel and pharmaceutical industries. In connection with the development of sustainable bioprocessing, it is a challenge to design and develop efficient Arthrospira cell factories which can certify effective conversion from the raw materials (i.e. CO2 and sun light into desired products. With the current availability of the genome sequences and metabolic models of Arthrospira, the development of Arthrospira factories can now be accelerated by means of systems biology and the metabolic engineering approach. Here, we review recent research involving the use of Arthrospira cell factories for industrial applications, as well as the exploitation of systems biology and the metabolic engineering approach for studying Arthrospira. The current status of genomics and proteomics through the development of the genome-scale metabolic model of Arthrospira, as well as the use of mathematical modeling to simulate the phenotypes resulting from the different metabolic engineering strategies are discussed. At the end, the perspective and future direction on Arthrospira cell factories for industrial biotechnology are presented.

  18. Thematic minireview series: cell biology of G protein signaling.

    Science.gov (United States)

    Dohlman, Henrik G

    2015-03-13

    This thematic series is on the topic of cell signaling from a cell biology perspective, with a particular focus on G proteins. G protein-coupled receptors (GPCRs, also known as seven-transmembrane receptors) are typically found at the cell surface. Upon agonist binding, these receptors will activate a GTP-binding G protein at the cytoplasmic face of the plasma membrane. Additionally, there is growing evidence that G proteins can also be activated by non-receptor binding partners, and they can signal from non-plasma membrane compartments. The production of second messengers at multiple, spatially distinct locations represents a type of signal encoding that has been largely neglected. The first minireview in the series describes biosensors that are being used to monitor G protein signaling events in live cells. The second describes the implementation of antibody-based biosensors to dissect endosome signaling by G proteins and their receptors. The third describes the function of a non-receptor, cytoplasmic activator of G protein signaling, called GIV (Girdin). Collectively, the advances described in these articles provide a deeper understanding and emerging opportunities for new pharmacology. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  19. Agent-Based Modeling in Molecular Systems Biology.

    Science.gov (United States)

    Soheilypour, Mohammad; Mofrad, Mohammad R K

    2018-06-08

    Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially-detailed and computationally-efficient approaches. In this review, we summarize the capabilities of agent-based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. © 2018 WILEY Periodicals, Inc.

  20. Autotaxin: Its Role in Biology of Melanoma Cells and as a Pharmacological Target

    Directory of Open Access Journals (Sweden)

    Maciej Jankowski

    2011-01-01

    Full Text Available Autotaxin (ATX is an extracellular lysophospholipase D (lysoPLD released from normal cells and cancer cells. Activity of ATX is detected in various biological fluids. The lysophosphatidic acid (LPA is the main product of ATX. LPA acting through specific G protein-coupled receptors (LPA1-LPA6 affects immunological response, normal development, and malignant tumors' formation and progression. In this review, the impact of autotoxin on biology of melanoma cells and potential treatment is discussed.

  1. Complex fluids in biological systems experiment, theory, and computation

    CERN Document Server

    2015-01-01

    This book serves as an introduction to the continuum mechanics and mathematical modeling of complex fluids in living systems. The form and function of living systems are intimately tied to the nature of surrounding fluid environments, which commonly exhibit nonlinear and history dependent responses to forces and displacements. With ever-increasing capabilities in the visualization and manipulation of biological systems, research on the fundamental phenomena, models, measurements, and analysis of complex fluids has taken a number of exciting directions. In this book, many of the world’s foremost experts explore key topics such as: Macro- and micro-rheological techniques for measuring the material properties of complex biofluids and the subtleties of data interpretation Experimental observations and rheology of complex biological materials, including mucus, cell membranes, the cytoskeleton, and blood The motility of microorganisms in complex fluids and the dynamics of active suspensions Challenges and solut...

  2. Biology and clinical application of CAR T cells for B cell malignancies.

    Science.gov (United States)

    Davila, Marco L; Sadelain, Michel

    2016-07-01

    Chimeric antigen receptor (CAR)-modified T cells have generated broad interest in oncology following a series of dramatic clinical successes in patients with chemorefractory B cell malignancies. CAR therapy now appears to be on the cusp of regulatory approval as a cell-based immunotherapy. We review here the T cell biology and cell engineering research that led to the development of second generation CARs, the selection of CD19 as a CAR target, and the preclinical studies in animal models that laid the foundation for clinical trials targeting CD19+ malignancies. We further summarize the status of CD19 CAR clinical therapy for non-Hodgkin lymphoma and B cell acute lymphoblastic leukemia, including their efficacy, toxicities (cytokine release syndrome, neurotoxicity and B cell aplasia) and current management in humans. We conclude with an overview of recent pre-clinical advances in CAR design that argues favorably for the advancement of CAR therapy to tackle other hematological malignancies as well as solid tumors.

  3. Dynamic cell culture system: a new cell cultivation instrument for biological experiments in space

    Science.gov (United States)

    Gmunder, F. K.; Nordau, C. G.; Tschopp, A.; Huber, B.; Cogoli, A.

    1988-01-01

    The prototype of a miniaturized cell cultivation instrument for animal cell culture experiments aboard Spacelab is presented (Dynamic cell culture system: DCCS). The cell chamber is completely filled and has a working volume of 200 microliters. Medium exchange is achieved with a self-powered osmotic pump (flowrate 1 microliter h-1). The reservoir volume of culture medium is 230 microliters. The system is neither mechanically stirred nor equipped with sensors. Hamster kidney (Hak) cells growing on Cytodex 3 microcarriers were used to test the biological performance of the DCCS. Growth characteristics in the DCCS, as judged by maximal cell density, glucose consumption, lactic acid secretion and pH, were similar to those in cell culture tubes.

  4. Nanoscopical dissection of ancestral nucleoli in Archaea: a case of study in Evolutionary Cell Biology

    KAUST Repository

    Islas Morales, Parsifal

    2018-01-01

    Evolutionary cell biology (ECB) has raised increasing attention in the last decades. Is this a new discipline and an historical opportunity to combine functional and evolutionary biology towards the insight that cell

  5. Teaching Cell and Molecular Biology for Gender Equity

    Science.gov (United States)

    Sible, Jill C.; Wilhelm, Dayna E.; Lederman, Muriel

    2006-01-01

    Science, technology, engineering, and math (STEM) fields, including cell biology, are characterized by the "leaky pipeline" syndrome in which, over time, women leave the discipline. The pipeline itself and the pond into which it empties may not be neutral. Explicating invisible norms, attitudes, and practices by integrating social…

  6. Tip cell overtaking occurs as a side effect of sprouting in computational models of angiogenesis.

    Science.gov (United States)

    Boas, Sonja E M; Merks, Roeland M H

    2015-11-21

    During angiogenesis, the formation of new blood vessels from existing ones, endothelial cells differentiate into tip and stalk cells, after which one tip cell leads the sprout. More recently, this picture has changed. It has become clear that endothelial cells compete for the tip position during angiogenesis: a phenomenon named tip cell overtaking. The biological function of tip cell overtaking is not yet known. From experimental observations, it is unclear to what extent tip cell overtaking is a side effect of sprouting or to what extent it is regulated through a VEGF-Dll4-Notch signaling network and thus might have a biological function. To address this question, we studied tip cell overtaking in computational models of angiogenic sprouting in absence and in presence of VEGF-Dll4-Notch signaling. We looked for tip cell overtaking in two existing Cellular Potts models of angiogenesis. In these simulation models angiogenic sprouting-like behavior emerges from a small set of plausible cell behaviors. In the first model, cells aggregate through contact-inhibited chemotaxis. In the second model the endothelial cells assume an elongated shape and aggregate through (non-inhibited) chemotaxis. In both these sprouting models the endothelial cells spontaneously migrate forwards and backwards within sprouts, suggesting that tip cell overtaking might occur as a side effect of sprouting. In accordance with other experimental observations, in our simulations the cells' tendency to occupy the tip position can be regulated when two cell lines with different levels of Vegfr2 expression are contributing to sprouting (mosaic sprouting assay), where cell behavior is regulated by a simple VEGF-Dll4-Notch signaling network. Our modeling results suggest that tip cell overtaking can occur spontaneously due to the stochastic motion of cells during sprouting. Thus, tip cell overtaking and sprouting dynamics may be interdependent and should be studied and interpreted in combination. VEGF

  7. An overview of bioinformatics methods for modeling biological pathways in yeast.

    Science.gov (United States)

    Hou, Jie; Acharya, Lipi; Zhu, Dongxiao; Cheng, Jianlin

    2016-03-01

    The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein-protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways inS. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  8. Neural crest cells: from developmental biology to clinical interventions.

    Science.gov (United States)

    Noisa, Parinya; Raivio, Taneli

    2014-09-01

    Neural crest cells are multipotent cells, which are specified in embryonic ectoderm in the border of neural plate and epiderm during early development by interconnection of extrinsic stimuli and intrinsic factors. Neural crest cells are capable of differentiating into various somatic cell types, including melanocytes, craniofacial cartilage and bone, smooth muscle, and peripheral nervous cells, which supports their promise for cell therapy. In this work, we provide a comprehensive review of wide aspects of neural crest cells from their developmental biology to applicability in medical research. We provide a simplified model of neural crest cell development and highlight the key external stimuli and intrinsic regulators that determine the neural crest cell fate. Defects of neural crest cell development leading to several human disorders are also mentioned, with the emphasis of using human induced pluripotent stem cells to model neurocristopathic syndromes. © 2014 Wiley Periodicals, Inc.

  9. Complex network problems in physics, computer science and biology

    Science.gov (United States)

    Cojocaru, Radu Ionut

    There is a close relation between physics and mathematics and the exchange of ideas between these two sciences are well established. However until few years ago there was no such a close relation between physics and computer science. Even more, only recently biologists started to use methods and tools from statistical physics in order to study the behavior of complex system. In this thesis we concentrate on applying and analyzing several methods borrowed from computer science to biology and also we use methods from statistical physics in solving hard problems from computer science. In recent years physicists have been interested in studying the behavior of complex networks. Physics is an experimental science in which theoretical predictions are compared to experiments. In this definition, the term prediction plays a very important role: although the system is complex, it is still possible to get predictions for its behavior, but these predictions are of a probabilistic nature. Spin glasses, lattice gases or the Potts model are a few examples of complex systems in physics. Spin glasses and many frustrated antiferromagnets map exactly to computer science problems in the NP-hard class defined in Chapter 1. In Chapter 1 we discuss a common result from artificial intelligence (AI) which shows that there are some problems which are NP-complete, with the implication that these problems are difficult to solve. We introduce a few well known hard problems from computer science (Satisfiability, Coloring, Vertex Cover together with Maximum Independent Set and Number Partitioning) and then discuss their mapping to problems from physics. In Chapter 2 we provide a short review of combinatorial optimization algorithms and their applications to ground state problems in disordered systems. We discuss the cavity method initially developed for studying the Sherrington-Kirkpatrick model of spin glasses. We extend this model to the study of a specific case of spin glass on the Bethe

  10. Relationship between α/β and radiosensitivity and biologic effect of fractional irradiation of tumor cells

    International Nuclear Information System (INIS)

    Guo Chuanling; Chinese Academy of Sciences, Beijing; Wang Jufang; Jin Xiaodong; Li Wenjian

    2006-01-01

    Five kinds of malignant human tumor cells, i.e. SMMC-7721, HeLa, A549, HT29 and PC3 cell lines, were irradiated by 60 Co γ-rays to 1-6 Gy in a single irradiation or two irradiations of half dose. The radiosensitivity was compared with the dose-survival curves and D 50 and D 10 values. Differences in the D 50 and D 10 between the single and fractional irradiation groups showed the effect of fractional irradiation. Except for PC3 cells, all the cell lines showed obvious relationship between radiosensitivity and biologic effect of fractional irradiation and the α/β value. A cell line with bigger α/β was more radiation sensitive, with less obvious effect of fractional irradiation. The results indicate that there were obvious differences in radiosensitivity, repair ability and biologic effect of fractional irradiation between tumor cells from different tissues. To some tumor cell lines, the relationship between radiosensitivity, biologic effect of fractional irradiation and repair ability was attested. The α/β value of single irradiation can be regarded as a parameter to investigate the radiosensitivity and biologic effect of fractional irradiation of tumor cells. (authors)

  11. Mycoplasma testing of cell substrates and biologics: Review of alternative non-microbiological techniques.

    Science.gov (United States)

    Volokhov, Dmitriy V; Graham, Laurie J; Brorson, Kurt A; Chizhikov, Vladimir E

    2011-01-01

    Mycoplasmas, particularly species of the genera Mycoplasma and Acholeplasma, are known to be occasional microbial contaminants of cell cultures that produce biologics. This presents a serious concern regarding the risk of mycoplasma contamination for research laboratories and commercial facilities developing and manufacturing cell-derived biological and biopharmaceutical products for therapeutic use. Potential undetected contamination of these products or process intermediates with mycoplasmas represents a potential safety risk for patients and a business risk for producers of biopharmaceuticals. To minimize these risks, monitoring for adventitious agents, such as viruses and mycoplasmas, is performed during the manufacture of biologics produced in cell culture substrates. The "gold standard" microbiological assay, currently recommended by the USP, EP, JP and the US FDA, for the mycoplasma testing of biologics, involves the culture of viable mycoplasmas in broth, agar plates and indicator cells. Although the procedure enables highly efficient mycoplasma detection in cell substrates and cell-derived products, the overall testing strategy is time consuming (a minimum of 28 days) and requires skilled interpretation of the results. The long time period required for these conventional assays does not permit their use for products with short shelf-lives or for timely 'go/no-go' decisions during routine in-process testing. PCR methodology has existed for decades, however PCR based and other alternative methods for mycoplasma detection have only recently been considered for application to biologics manufacture. The application of alternative nucleic acid-based, enzyme-based and/or recombinant cell-culture methods, particularly in combination with efficient sample preparation procedures, could provide advantages over conventional microbiological methods in terms of analytical throughput, simplicity, and turnaround time. However, a challenge to the application of alternative

  12. Cell-free protein synthesis enabled rapid prototyping for metabolic engineering and synthetic biology

    Directory of Open Access Journals (Sweden)

    Lihong Jiang

    2018-06-01

    Full Text Available Advances in metabolic engineering and synthetic biology have facilitated the manufacturing of many valuable-added compounds and commodity chemicals using microbial cell factories in the past decade. However, due to complexity of cellular metabolism, the optimization of metabolic pathways for maximal production represents a grand challenge and an unavoidable barrier for metabolic engineering. Recently, cell-free protein synthesis system (CFPS has been emerging as an enabling alternative to address challenges in biomanufacturing. This review summarizes the recent progresses of CFPS in rapid prototyping of biosynthetic pathways and genetic circuits (biosensors to speed up design-build-test (DBT cycles of metabolic engineering and synthetic biology. Keywords: Cell-free protein synthesis, Metabolic pathway optimization, Genetic circuits, Metabolic engineering, Synthetic biology

  13. Micrasterias as a model system in plant cell biology

    Directory of Open Access Journals (Sweden)

    Ursula Luetz-Meindl

    2016-07-01

    Full Text Available The unicellular freshwater alga Micrasterias denticulata is an exceptional organism due to its extraordinary star-shaped, highly symmetric morphology and has thus attracted the interest of researchers for many decades. As a member of the Streptophyta, Micrasterias is not only genetically closely related to higher land plants but shares common features with them in many physiological and cell biological aspects. These facts, together with its considerable cell size of about 200 µm, its modest cultivation conditions and the uncomplicated accessibility particularly to any microscopic techniques, make Micrasterias a very well suited cell biological plant model system. The review focuses particularly on cell wall formation and composition, dictyosomal structure and function, cytoskeleton control of growth and morphogenesis as well as on ionic regulation and signal transduction. It has been also shown in the recent years that Micrasterias is a highly sensitive indicator for environmental stress impact such as heavy metals, high salinity, oxidative stress or starvation. Stress induced organelle degradation, autophagy, adaption and detoxification mechanisms have moved in the center of interest and have been investigated with modern microscopic techniques such as 3-D- and analytical electron microscopy as well as with biochemical, physiological and molecular approaches. This review is intended to summarize and discuss the most important results obtained in Micrasterias in the last 20 years and to compare the results to similar processes in higher plant cells.

  14. G-LoSA: An efficient computational tool for local structure-centric biological studies and drug design.

    Science.gov (United States)

    Lee, Hui Sun; Im, Wonpil

    2016-04-01

    Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G-LoSA. G-LoSA aligns protein local structures in a sequence order independent way and provides a GA-score, a chemical feature-based and size-independent structure similarity score. Our benchmark validation shows the robust performance of G-LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure-centric comparative biology studies. In particular, G-LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G-LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer-aided drug design. We hope that G-LoSA can be a useful computational method for exploring interesting biological problems through large-scale comparison of protein local structures and facilitating drug discovery research and development. G-LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. © 2016 The Protein Society.

  15. Multiple-Swarm Ensembles: Improving the Predictive Power and Robustness of Predictive Models and Its Use in Computational Biology.

    Science.gov (United States)

    Alves, Pedro; Liu, Shuang; Wang, Daifeng; Gerstein, Mark

    2018-01-01

    Machine learning is an integral part of computational biology, and has already shown its use in various applications, such as prognostic tests. In the last few years in the non-biological machine learning community, ensembling techniques have shown their power in data mining competitions such as the Netflix challenge; however, such methods have not found wide use in computational biology. In this work, we endeavor to show how ensembling techniques can be applied to practical problems, including problems in the field of bioinformatics, and how they often outperform other machine learning techniques in both predictive power and robustness. Furthermore, we develop a methodology of ensembling, Multi-Swarm Ensemble (MSWE) by using multiple particle swarm optimizations and demonstrate its ability to further enhance the performance of ensembles.

  16. RISE OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY IN INDIA: A LOOK THROUGH PUBLICATIONS

    Directory of Open Access Journals (Sweden)

    Anjali Srivastava

    2017-09-01

    Full Text Available Computational biology and bioinformatics have been part and parcel of biomedical research for few decades now. However, the institutionalization of bioinformatics research took place with the establishment of Distributed Information Centres (DISCs in the research institutions of repute in various disciplines by the Department of Biotechnology, Government of India. Though, at initial stages, this endeavor was mainly focused on providing infrastructure for using information technology and internet based communication and tools for carrying out computational biology and in-silico assisted research in varied arena of research starting from disease biology to agricultural crops, spices, veterinary science and many more, the natural outcome of establishment of such facilities resulted into new experiments with bioinformatics tools. Thus, Biotechnology Information Systems (BTIS grew into a solid movement and a large number of publications started coming out of these centres. In the end of last century, bioinformatics started developing like a full-fledged research subject. In the last decade, a need was felt to actually make a factual estimation of the result of this endeavor of DBT which had, by then, established about two hundred centres in almost all disciplines of biomedical research. In a bid to evaluate the efforts and outcome of these centres, BTIS Centre at CSIR-CDRI, Lucknow was entrusted with collecting and collating the publications of these centres. However, when the full data was compiled, the DBT task force felt that the study must include Non-BTIS centres also so as to expand the report to have a glimpse of bioinformatics publications from the country.

  17. Biochemistry and biology: heart-to-heart to investigate cardiac progenitor cells.

    Science.gov (United States)

    Chimenti, Isotta; Forte, Elvira; Angelini, Francesco; Messina, Elisa; Giacomello, Alessandro

    2013-02-01

    Cardiac regenerative medicine is a rapidly evolving field, with promising future developments for effective personalized treatments. Several stem/progenitor cells are candidates for cardiac cell therapy, and emerging evidence suggests how multiple metabolic and biochemical pathways strictly regulate their fate and renewal. In this review, we will explore a selection of areas of common interest for biology and biochemistry concerning stem/progenitor cells, and in particular cardiac progenitor cells. Numerous regulatory mechanisms have been identified that link stem cell signaling and functions to the modulation of metabolic pathways, and vice versa. Pharmacological treatments and culture requirements may be exploited to modulate stem cell pluripotency and self-renewal, possibly boosting their regenerative potential for cell therapy. Mitochondria and their many related metabolites and messengers, such as oxygen, ROS, calcium and glucose, have a crucial role in regulating stem cell fate and the balance of their functions, together with many metabolic enzymes. Furthermore, protein biochemistry and proteomics can provide precious clues on the definition of different progenitor cell populations, their physiology and their autocrine/paracrine regulatory/signaling networks. Interdisciplinary approaches between biology and biochemistry can provide productive insights on stem/progenitor cells, allowing the development of novel strategies and protocols for effective cardiac cell therapy clinical translation. This article is part of a Special Issue entitled Biochemistry of Stem Cells. Copyright © 2012 Elsevier B.V. All rights reserved.

  18. Integrative multicellular biological modeling: a case study of 3D epidermal development using GPU algorithms

    Directory of Open Access Journals (Sweden)

    Christley Scott

    2010-08-01

    Full Text Available Abstract Background Simulation of sophisticated biological models requires considerable computational power. These models typically integrate together numerous biological phenomena such as spatially-explicit heterogeneous cells, cell-cell interactions, cell-environment interactions and intracellular gene networks. The recent advent of programming for graphical processing units (GPU opens up the possibility of developing more integrative, detailed and predictive biological models while at the same time decreasing the computational cost to simulate those models. Results We construct a 3D model of epidermal development and provide a set of GPU algorithms that executes significantly faster than sequential central processing unit (CPU code. We provide a parallel implementation of the subcellular element method for individual cells residing in a lattice-free spatial environment. Each cell in our epidermal model includes an internal gene network, which integrates cellular interaction of Notch signaling together with environmental interaction of basement membrane adhesion, to specify cellular state and behaviors such as growth and division. We take a pedagogical approach to describing how modeling methods are efficiently implemented on the GPU including memory layout of data structures and functional decomposition. We discuss various programmatic issues and provide a set of design guidelines for GPU programming that are instructive to avoid common pitfalls as well as to extract performance from the GPU architecture. Conclusions We demonstrate that GPU algorithms represent a significant technological advance for the simulation of complex biological models. We further demonstrate with our epidermal model that the integration of multiple complex modeling methods for heterogeneous multicellular biological processes is both feasible and computationally tractable using this new technology. We hope that the provided algorithms and source code will be a

  19. Biology of teeth and implants: Host factors - pathology, regeneration, and the role of stem cells.

    Science.gov (United States)

    Eggert, F-Michael; Levin, Liran

    2018-01-01

    In chronic periodontitis and peri-implantitis, cells of the innate and adaptive immune systems are involved directly in the lesions within the tissues of the patient. Absence of a periodontal ligament around implants does not prevent a biologic process similar to that of periodontitis from affecting osseointegration. Our first focus is on factors in the biology of individuals that are responsible for the susceptibility of such individuals to chronic periodontitis and to peri-implantitis. Genetic factors are of significant importance in susceptibility to these diseases. Genetic factors of the host affect the composition of the oral microbiome in the same manner that they influence other microbiomes, such as those of the intestines and of the lungs. Our second focus is on the central role of stem cells in tissue regeneration, in the functioning of innate and adaptive immune systems, and in metabolism of bone. Epithelial cell rests of Malassez (ERM) are stem cells of epithelial origin that maintain the periodontal ligament as well as the cementum and alveolar bone associated with the ligament. The tissue niche within which ERM are found extends into the supracrestal areas of collagen fiber-containing tissues of the gingivae above the bony alveolar crest. Maintenance and regeneration of all periodontal tissues involves the activity of a variety of stem cells. The success of dental implants indicates that important groups of stem cells in the periodontium are active to enable that biologic success. Successful replantation of avulsed teeth and auto-transplantation of teeth is comparable to placing dental implants, and so must also involve periodontal stem cells. Biology of teeth and biology of implants represents the biology of the various stem cells that inhabit specialized niches within the periodontal tissues. Diverse biologic processes must function together successfully to maintain periodontal health. Osseointegration of dental implants does not involve formation of

  20. The Promises of Biology and the Biology of Promises

    DEFF Research Database (Denmark)

    Lee, Jieun

    2015-01-01

    commitments with differently imagined futures. I argue that promises are constitutive of the stem cell biology, rather than being derivative of it. Since the biological concept of stem cells is predicated on the future that they promise, the biological life of stem cells is inextricably intertwined...... patients’ bodies in anticipation of materializing the promises of stem cell biology, they are produced as a new form of biovaluable. The promises of biology move beyond the closed circuit of scientific knowledge production, and proliferate in the speculative marketplaces of promises. Part II looks at how...... of technologized biology and biological time can appear promising with the backdrop of the imagined intransigence of social, political, and economic order in the Korean society....

  1. Wood smoke particle sequesters cell iron to impact a biological effect.

    Science.gov (United States)

    The biological effect of an inorganic particle (i.e., silica) can be associated with a disruption in cell iron homeostasis. Organic compounds included in particles originating from combustion processes can also complex sources of host cell iron to disrupt metal homeostasis. We te...

  2. Insights into female germ cell biology: from in vivo development to in vitro derivations.

    Science.gov (United States)

    Jung, Dajung; Kee, Kehkooi

    2015-01-01

    Understanding the mechanisms of human germ cell biology is important for developing infertility treatments. However, little is known about the mechanisms that regulate human gametogenesis due to the difficulties in collecting samples, especially germ cells during fetal development. In contrast to the mitotic arrest of spermatogonia stem cells in the fetal testis, female germ cells proceed into meiosis and began folliculogenesis in fetal ovaries. Regulations of these developmental events, including the initiation of meiosis and the endowment of primordial follicles, remain an enigma. Studying the molecular mechanisms of female germ cell biology in the human ovary has been mostly limited to spatiotemporal characterizations of genes or proteins. Recent efforts in utilizing in vitro differentiation system of stem cells to derive germ cells have allowed researchers to begin studying molecular mechanisms during human germ cell development. Meanwhile, the possibility of isolating female germline stem cells in adult ovaries also excites researchers and generates many debates. This review will mainly focus on presenting and discussing recent in vivo and in vitro studies on female germ cell biology in human. The topics will highlight the progress made in understanding the three main stages of germ cell developments: namely, primordial germ cell formation, meiotic initiation, and folliculogenesis.

  3. Cellular Analysis of Adult Neural Stem Cells for Investigating Prion Biology.

    Science.gov (United States)

    Haigh, Cathryn L

    2017-01-01

    Traditional primary and secondary cell cultures have been used for the investigation of prion biology and disease for many years. While both types of cultures produce highly valid and immensely valuable results, they also have their limitations; traditional cell lines are often derived from cancers, therefore subject to numerous DNA changes, and primary cultures are labor-intensive and expensive to produce requiring sacrifice of many animals. Neural stem cell (NSC) cultures are a relatively new technology to be used for the study of prion biology and disease. While NSCs are subject to their own limitations-they are generally cultured ex vivo in environments that artificially force their growth-they also have their own unique advantages. NSCs retain the ability for self-renewal and can therefore be propagated in culture similarly to secondary cultures without genetic manipulation. In addition, NSCs are multipotent; they can be induced to differentiate into mature cells of central nervous system (CNS) linage. The combination of self-renewal and multipotency allows NSCs to be used as a primary cell line over multiple generations saving time, costs, and animal harvests, thus providing a valuable addition to the existing cell culture repertoire used for investigation of prion biology and disease. Furthermore, NSC cultures can be generated from mice of any genotype, either by embryonic harvest or harvest from adult brain, allowing gene expression to be studied without further genetic manipulation. This chapter describes a standard method of culturing adult NSCs and assays for monitoring NSC growth, migration, and differentiation and revisits basic reactive oxygen species detection in the context of NSC cultures.

  4. Development of an Instrument for Measuring Self-Efficacy in Cell Biology

    Science.gov (United States)

    Reeve, Suzanne; Kitchen, Elizabeth; Sudweeks, Richard R.; Bell, John D.; Bradshaw, William S.

    2011-01-01

    This article describes the development of a ten-item scale to assess biology majors' self-efficacy towards the critical thinking and data analysis skills taught in an upper-division cell biology course. The original seven-item scale was expanded to include three additional items based on the results of item analysis. Evidence of reliability and…

  5. Biological characteristics of human-urine-derived stem cells: potential for cell-based therapy in neurology.

    Science.gov (United States)

    Guan, Jun-Jie; Niu, Xin; Gong, Fei-Xiang; Hu, Bin; Guo, Shang-Chun; Lou, Yuan-Lei; Zhang, Chang-Qing; Deng, Zhi-Feng; Wang, Yang

    2014-07-01

    Stem cells in human urine have gained attention in recent years; however, urine-derived stem cells (USCs) are far from being well elucidated. In this study, we compared the biological characteristics of USCs with adipose-derived stem cells (ASCs) and investigated whether USCs could serve as a potential cell source for neural tissue engineering. USCs were isolated from voided urine with a modified culture medium. Through a series of experiments, we examined the growth rate, surface antigens, and differentiation potential of USCs, and compared them with ASCs. USCs showed robust proliferation ability. After serial propagation, USCs retained normal karyotypes. Cell surface antigen expression of USCs was similar to ASCs. With lineage-specific induction factors, USCs could differentiate toward the osteogenic, chondrogenic, adipogenic, and neurogenic lineages. To assess the ability of USCs to survive, differentiate, and migrate, they were seeded onto hydrogel scaffold and transplanted into rat brain. The results showed that USCs were able to survive in the lesion site, migrate to other areas, and express proteins that were associated with neural phenotypes. The results of our study demonstrate that USCs possess similar biological characteristics with ASCs and have multilineage differentiation potential. Moreover USCs can differentiate to neuron-like cells in rat brain. The present study shows that USCs are a promising cell source for tissue engineering and regenerative medicine.

  6. Evolving a lingua franca and associated software infrastructure for computational systems biology: the Systems Biology Markup Language (SBML) project.

    Science.gov (United States)

    Hucka, M; Finney, A; Bornstein, B J; Keating, S M; Shapiro, B E; Matthews, J; Kovitz, B L; Schilstra, M J; Funahashi, A; Doyle, J C; Kitano, H

    2004-06-01

    Biologists are increasingly recognising that computational modelling is crucial for making sense of the vast quantities of complex experimental data that are now being collected. The systems biology field needs agreed-upon information standards if models are to be shared, evaluated and developed cooperatively. Over the last four years, our team has been developing the Systems Biology Markup Language (SBML) in collaboration with an international community of modellers and software developers. SBML has become a de facto standard format for representing formal, quantitative and qualitative models at the level of biochemical reactions and regulatory networks. In this article, we summarise the current and upcoming versions of SBML and our efforts at developing software infrastructure for supporting and broadening its use. We also provide a brief overview of the many SBML-compatible software tools available today.

  7. Can molecular cell biology explain chromosome motions?

    Directory of Open Access Journals (Sweden)

    Gagliardi L

    2011-05-01

    Full Text Available Abstract Background Mitotic chromosome motions have recently been correlated with electrostatic forces, but a lingering "molecular cell biology" paradigm persists, proposing binding and release proteins or molecular geometries for force generation. Results Pole-facing kinetochore plates manifest positive charges and interact with negatively charged microtubule ends providing the motive force for poleward chromosome motions by classical electrostatics. This conceptual scheme explains dynamic tracking/coupling of kinetochores to microtubules and the simultaneous depolymerization of kinetochore microtubules as poleward force is generated. Conclusion We question here why cells would prefer complex molecular mechanisms to move chromosomes when direct electrostatic interactions between known bound charge distributions can accomplish the same task much more simply.

  8. Evolving cell models for systems and synthetic biology.

    Science.gov (United States)

    Cao, Hongqing; Romero-Campero, Francisco J; Heeb, Stephan; Cámara, Miguel; Krasnogor, Natalio

    2010-03-01

    This paper proposes a new methodology for the automated design of cell models for systems and synthetic biology. Our modelling framework is based on P systems, a discrete, stochastic and modular formal modelling language. The automated design of biological models comprising the optimization of the model structure and its stochastic kinetic constants is performed using an evolutionary algorithm. The evolutionary algorithm evolves model structures by combining different modules taken from a predefined module library and then it fine-tunes the associated stochastic kinetic constants. We investigate four alternative objective functions for the fitness calculation within the evolutionary algorithm: (1) equally weighted sum method, (2) normalization method, (3) randomly weighted sum method, and (4) equally weighted product method. The effectiveness of the methodology is tested on four case studies of increasing complexity including negative and positive autoregulation as well as two gene networks implementing a pulse generator and a bandwidth detector. We provide a systematic analysis of the evolutionary algorithm's results as well as of the resulting evolved cell models.

  9. Cell Culture in Microgravity: Opening the Door to Space Cell Biology

    Science.gov (United States)

    Pellis, Neal R.; Dawson, David L. (Technical Monitor)

    1999-01-01

    Adaptational response of human cell populations to microgravity is investigated using simulation, short-term Shuttle experiments, and long-term microgravity. Simulation consists of a clinostatically-rotated cell culture system. The system is a horizontally-rotated cylinder completely filled with culture medium. Low speed rotation results in continuous-fall of the cells through the fluid medium. In this setting, cells: 1) aggregate, 2) propagate in three dimensions, 3) synthesize matrix, 4) differentiate, and 5) form sinusoids that facilitate mass transfer. Space cell culture is conducted in flight bioreactors and in static incubators. Cells grown in microgravity are: bovine cartilage, promyelocytic leukemia, kidney proximal tubule cells, adrenal medulla, breast and colon cancer, and endothelium. Cells were cultured in space to test specific hypotheses. Cartilage cells were used to determine structural differences in cartilage grown in space compared to ground-based bioreactors. Results from a 130-day experiment on Mir revealed that cartilage grown in space was substantially more compressible due to insufficient glycosaminoglycan in the matrix. Interestingly, earth-grown cartilage conformed better to the dimensions of the scaffolding material, while the Mir specimens were spherical. The other cell populations are currently being analyzed for cell surface properties, gene expression, and differentiation. Results suggest that some cells spontaneously differentiate in microgravity. Additionally, vast changes in gene expression may occur in response to microgravity. In conclusion, the transition to microgravity may constitute a physical perturbation in cells resulting in unique gene expressions, the consequences of which may be useful in tissue engineering, disease modeling, and space cell biology.

  10. Laser apparatus and method for microscopic and spectroscopic analysis and processing of biological cells

    Science.gov (United States)

    Gourley, P.L.; Gourley, M.F.

    1997-03-04

    An apparatus and method are disclosed for microscopic and spectroscopic analysis and processing of biological cells. The apparatus comprises a laser having an analysis region within the laser cavity for containing one or more biological cells to be analyzed. The presence of a cell within the analysis region in superposition with an activated portion of a gain medium of the laser acts to encode information about the cell upon the laser beam, the cell information being recoverable by an analysis means that preferably includes an array photodetector such as a CCD camera and a spectrometer. The apparatus and method may be used to analyze biomedical cells including blood cells and the like, and may include processing means for manipulating, sorting, or eradicating cells after analysis. 20 figs.

  11. The cell biology of Tobacco mosaic virus replication and movement

    Directory of Open Access Journals (Sweden)

    Chengke eLiu

    2013-02-01

    Full Text Available Successful systemic infection of a plant by Tobacco mosaic virus (TMV requires three processes that repeat over time: initial establishment and accumulation in invaded cells, intercellular movement and systemic transport. Accumulation and intercellular movement of TMV necessarily involves intracellular transport by complexes containing virus and host proteins and virus RNA during a dynamic process that can be visualized. Multiple membranes appear to assist TMV accumulation, while membranes, microfilaments and microtubules appear to assist TMV movement. Here we review cell biological studies that describe TMV-membrane, -cytoskeleton and -other host protein interactions which influence virus accumulation and movement in leaves and callus tissue. The importance of understanding the developmental phase of the infection in relationship to the observed virus-membrane or -host protein interaction is emphasized. Utilizing the latest observations of TMV-membrane and -host protein interactions within our evolving understanding of the infection ontogeny, a model for TMV accumulation and intracellular spread in a cell biological context is provided.

  12. COMPUTATIONAL MODELING AND SIMULATION IN BIOLOGY TEACHING: A MINIMALLY EXPLORED FIELD OF STUDY WITH A LOT OF POTENTIAL

    Directory of Open Access Journals (Sweden)

    Sonia López

    2016-09-01

    Full Text Available This study is part of a research project that aims to characterize the epistemological, psychological and didactic presuppositions of science teachers (Biology, Physics, Chemistry that implement Computational Modeling and Simulation (CMS activities as a part of their teaching practice. We present here a synthesis of a literature review on the subject, evidencing how in the last two decades this form of computer usage for science teaching has boomed in disciplines such as Physics and Chemistry, but in a lesser degree in Biology. Additionally, in the works that dwell on the use of CMS in Biology, we identified a lack of theoretical bases that support their epistemological, psychological and/or didactic postures. Accordingly, this generates significant considerations for the fields of research and teacher instruction in Science Education.

  13. The time is right: proteome biology of stem cells.

    NARCIS (Netherlands)

    Whetton, A.D.; Williamson, A.J.K.; Krijgsveld, J.; Lee, B.H.; Lemischka, I.; Oh, S.; Pera, M.; Mummery, C.L.; Heck, A.J.R.

    2008-01-01

    In stem cell biology, there is a growing need for advanced technologies that may help to unravel the molecular mechanisms of self-renewal and differentiation. Proteomics, the comprehensive analysis of proteins, is such an emerging technique. To facilitate interactions between specialists in

  14. Human mesenchymal stromal cells : biological characterization and clinical application

    NARCIS (Netherlands)

    Bernardo, Maria Ester

    2010-01-01

    This thesis focuses on the characterization of the biological and functional properties of human mesenchymal stromal cells (MSCs), isolated from different tissue sources. The differentiation capacity of MSCs from fetal and adult tissues has been tested and compared. Umbilical cord blood (UCB) has

  15. COMPUTATIONAL MODELING OF SIGNALING PATHWAYS MEDIATING CELL CYCLE AND APOPTOTIC RESPONSES TO IONIZING RADIATION MEDIATED DNA DAMAGE

    Science.gov (United States)

    Demonstrated of the use of a computational systems biology approach to model dose response relationships. Also discussed how the biologically motivated dose response models have only limited reference to the underlying molecular level. Discussed the integration of Computational S...

  16. Using a Module-Based Laboratory to Incorporate Inquiry into a Large Cell Biology Course

    Science.gov (United States)

    Howard, David R.; Miskowski, Jennifer A.

    2005-01-01

    Because cell biology has rapidly increased in breadth and depth, instructors are challenged not only to provide undergraduate science students with a strong, up-to-date foundation of knowledge, but also to engage them in the scientific process. To these ends, revision of the Cell Biology Lab course at the University of Wisconsin-La Crosse was…

  17. Radiation damage and repair in cells and cell components. Part 2. Physical radiations and biological significance. Final report

    International Nuclear Information System (INIS)

    Fluke, D.J.

    1984-08-01

    The report comprises a teaching text, encompassing all physical radiations likely to be of biological interest, and the relevant biological effects and their significance. Topics include human radiobiology, delayed effects, radiation absorption in organisms, aqueous radiation chemistry, cell radiobiology, mutagenesis, and photobiology

  18. Cell migration analysis: A low-cost laboratory experiment for cell and developmental biology courses using keratocytes from fish scales.

    Science.gov (United States)

    Prieto, Daniel; Aparicio, Gonzalo; Sotelo-Silveira, Jose R

    2017-11-01

    Cell and developmental processes are complex, and profoundly dependent on spatial relationships that change over time. Innovative educational or teaching strategies are always needed to foster deep comprehension of these processes and their dynamic features. However, laboratory exercises in cell and developmental biology at the undergraduate level do not often take into account the time dimension. In this article, we provide a laboratory exercise focused in cell migration, aiming to stimulate thinking in time and space dimensions through a simplification of more complex processes occurring in cell or developmental biology. The use of open-source tools for the analysis, as well as the whole package of raw results (available at http://github.com/danielprieto/keratocyte) make it suitable for its implementation in courses with very diverse budgets. Aiming to facilitate the student's transition from science-students to science-practitioners we propose an exercise of scientific thinking, and an evaluation method. This in turn is communicated here to facilitate the finding of common caveats and weaknesses in the process of producing simple scientific communications describing the results achieved. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(6):475-482, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

  19. Human Embryonic Kidney 293 Cells: A Vehicle for Biopharmaceutical Manufacturing, Structural Biology, and Electrophysiology.

    Science.gov (United States)

    Hu, Jianwen; Han, Jizhong; Li, Haoran; Zhang, Xian; Liu, Lan Lan; Chen, Fei; Zeng, Bin

    2018-01-01

    Mammalian cells, e.g., CHO, BHK, HEK293, HT-1080, and NS0 cells, represent important manufacturing platforms in bioengineering. They are widely used for the production of recombinant therapeutic proteins, vaccines, anticancer agents, and other clinically relevant drugs. HEK293 (human embryonic kidney 293) cells and their derived cell lines provide an attractive heterologous system for the development of recombinant proteins or adenovirus productions, not least due to their human-like posttranslational modification of protein molecules to provide the desired biological activity. Secondly, they also exhibit high transfection efficiency yielding high-quality recombinant proteins. They are easy to maintain and express with high fidelity membrane proteins, such as ion channels and transporters, and thus are attractive for structural biology and electrophysiology studies. In this article, we review the literature on HEK293 cells regarding their origins but also stress their advancements into the different cell lines engineered and discuss some significant aspects which make them versatile systems for biopharmaceutical manufacturing, drug screening, structural biology research, and electrophysiology applications. © 2018 S. Karger AG, Basel.

  20. 10 years for the Journal of Bioinformatics and Computational Biology (2003-2013) -- a retrospective.

    Science.gov (United States)

    Eisenhaber, Frank; Sherman, Westley Arthur

    2014-06-01

    The Journal of Bioinformatics and Computational Biology (JBCB) started publishing scientific articles in 2003. It has established itself as home for solid research articles in the field (~ 60 per year) that are surprisingly well cited. JBCB has an important function as alternative publishing channel in addition to other, bigger journals.

  1. Systems and synthetic biology approaches to alter plant cell walls and reduce biomass recalcitrance.

    Science.gov (United States)

    Kalluri, Udaya C; Yin, Hengfu; Yang, Xiaohan; Davison, Brian H

    2014-12-01

    Fine-tuning plant cell wall properties to render plant biomass more amenable to biofuel conversion is a colossal challenge. A deep knowledge of the biosynthesis and regulation of plant cell wall and a high-precision genome engineering toolset are the two essential pillars of efforts to alter plant cell walls and reduce biomass recalcitrance. The past decade has seen a meteoric rise in use of transcriptomics and high-resolution imaging methods resulting in fresh insights into composition, structure, formation and deconstruction of plant cell walls. Subsequent gene manipulation approaches, however, commonly include ubiquitous mis-expression of a single candidate gene in a host that carries an intact copy of the native gene. The challenges posed by pleiotropic and unintended changes resulting from such an approach are moving the field towards synthetic biology approaches. Synthetic biology builds on a systems biology knowledge base and leverages high-precision tools for high-throughput assembly of multigene constructs and pathways, precision genome editing and site-specific gene stacking, silencing and/or removal. Here, we summarize the recent breakthroughs in biosynthesis and remodelling of major secondary cell wall components, assess the impediments in obtaining a systems-level understanding and explore the potential opportunities in leveraging synthetic biology approaches to reduce biomass recalcitrance. Published 2014. This article is a U.S. Government work and is in the public domain in the USA. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

  2. Student Perceptions of the Cell Biology Laboratory Learning Environment in Four Undergraduate Science Courses in Spain

    Science.gov (United States)

    De Juan, Joaquin; Pérez-Cañaveras, Rosa M.; Segovia, Yolanda; Girela, Jose Luis; Martínez-Ruiz, Noemi; Romero-Rameta, Alejandro; Gómez-Torres, Maria José; Vizcaya-Moreno, M. Flores

    2016-01-01

    Cell biology is an academic discipline that organises and coordinates the learning of the structure, function and molecular composition of cells in some undergraduate biomedical programs. Besides course content and teaching methodologies, the laboratory environment is considered a key element in the teaching of and learning of cell biology. The…

  3. Programmable full-adder computations in communicating three-dimensional cell cultures.

    Science.gov (United States)

    Ausländer, David; Ausländer, Simon; Pierrat, Xavier; Hellmann, Leon; Rachid, Leila; Fussenegger, Martin

    2018-01-01

    Synthetic biologists have advanced the design of trigger-inducible gene switches and their assembly into input-programmable circuits that enable engineered human cells to perform arithmetic calculations reminiscent of electronic circuits. By designing a versatile plug-and-play molecular-computation platform, we have engineered nine different cell populations with genetic programs, each of which encodes a defined computational instruction. When assembled into 3D cultures, these engineered cell consortia execute programmable multicellular full-adder logics in response to three trigger compounds.

  4. On the Modelling of Biological Patterns with Mechanochemical Models: Insights from Analysis and Computation

    KAUST Repository

    Moreo, P.; Gaffney, E. A.; Garcí a-Aznar, J. M.; Doblaré , M.

    2009-01-01

    The diversity of biological form is generated by a relatively small number of underlying mechanisms. Consequently, mathematical and computational modelling can, and does, provide insight into how cellular level interactions ultimately give rise

  5. Recent advances in the cell biology of aging.

    Science.gov (United States)

    Hayflick, L

    1980-01-01

    Cultured normal human and animal cells are predestined to undergo irreversible functional decrements that mimic age changes in the whole organism. When normal human embryonic fibroblasts are cultured in vitro, 50 +/- 10 population doublings occur. This maximum potential is diminished in cells derived from older donors and appears to be inversely proportional to their age. The 50 population doubling limit can account for all cells produced during a lifetime. The limitation on doubling potential of cultured normal cells is also expressed in vivo when serial transplants are made. There may be a direct correlation between the mean maximum life spans of several species and the population doubling potential of their cultured cells. A plethora of functional decrements occurs in cultured normal cells as they approach their maximum division capability. Many of these decrements are similar to those occurring in intact animals as they age. We have concluded that these functional decrements expressed in vitro, rather than cessation of cell division, are the essential contributors to age changes in intact animals. Thus, the study of events leading to functional losses in cultured normal cells may provide useful insights into the biology of aging.

  6. Networks in Cell Biology

    Science.gov (United States)

    Buchanan, Mark; Caldarelli, Guido; De Los Rios, Paolo; Rao, Francesco; Vendruscolo, Michele

    2010-05-01

    Introduction; 1. Network views of the cell Paolo De Los Rios and Michele Vendruscolo; 2. Transcriptional regulatory networks Sarath Chandra Janga and M. Madan Babu; 3. Transcription factors and gene regulatory networks Matteo Brilli, Elissa Calistri and Pietro Lió; 4. Experimental methods for protein interaction identification Peter Uetz, Björn Titz, Seesandra V. Rajagopala and Gerard Cagney; 5. Modeling protein interaction networks Francesco Rao; 6. Dynamics and evolution of metabolic networks Daniel Segré; 7. Hierarchical modularity in biological networks: the case of metabolic networks Erzsébet Ravasz Regan; 8. Signalling networks Gian Paolo Rossini; Appendix 1. Complex networks: from local to global properties D. Garlaschelli and G. Caldarelli; Appendix 2. Modelling the local structure of networks D. Garlaschelli and G. Caldarelli; Appendix 3. Higher-order topological properties S. Ahnert, T. Fink and G. Caldarelli; Appendix 4. Elementary mathematical concepts A. Gabrielli and G. Caldarelli; References.

  7. Cell Science and Cell Biology Research at MSFC: Summary

    Science.gov (United States)

    2003-01-01

    The common theme of these research programs is that they investigate regulation of gene expression in cells, and ultimately gene expression is controlled by the macromolecular interactions between regulatory proteins and DNA. The NASA Critical Path Roadmap identifies Muscle Alterations and Atrophy and Radiation Effects as Very Serious Risks and Severe Risks, respectively, in long term space flights. The specific problem addressed by Dr. Young's research ("Skeletal Muscle Atrophy and Muscle Cell Signaling") is that skeletal muscle loss in space cannot be prevented by vigorous exercise. Aerobic skeletal muscles (i.e., red muscles) undergo the most extensive atrophy during long-term space flight. Of the many different potential avenues for preventing muscle atrophy, Dr. Young has chosen to study the beta-adrenergic receptor (betaAR) pathway. The reason for this choice is that a family of compounds called betaAR agonists will preferentially cause an increase in muscle mass of aerobic muscles (i.e., red muscle) in animals, potentially providing a specific pharmacological solution to muscle loss in microgravity. In addition, muscle atrophy is a widespread medical problem in neuromuscular diseases, spinal cord injury, lack of exercise, aging, and any disease requiring prolonged bedridden status. Skeletal muscle cells in cell culture are utilized as a model system to study this problem. Dr. Richmond's research ("Radiation & Cancer Biology of Mammary Cells in Culture") is directed toward developing a laboratory model for use in risk assessment of cancer caused by space radiation. This research is unique because a human model will be developed utilizing human mammary cells that are highly susceptible to tumor development. This approach is preferential over using animal cells because of problems in comparing radiation-induced cancers between humans and animals.

  8. Cell-Selective Biological Activity of Rhodium Metalloinsertors Correlates with Subcellular Localization

    Science.gov (United States)

    Komor, Alexis C.; Schneider, Curtis J.; Weidmann, Alyson G.; Barton, Jacqueline K.

    2013-01-01

    Deficiencies in the mismatch repair (MMR) pathway are associated with several types of cancers, as well as resistance to commonly used chemotherapeutics. Rhodium metalloinsertors have been found to bind DNA mismatches with high affinity and specificity in vitro, and also exhibit cell-selective cytotoxicity, targeting MMR-deficient cells over MMR-proficient cells. Ten distinct metalloinsertors with varying lipophilicities have been synthesized and their mismatch binding affinities and biological activities determined. Although DNA photocleavage experiments demonstrate that their binding affinities are quite similar, their cell-selective antiproliferative and cytotoxic activities vary significantly. Inductively coupled plasma mass spectrometry (ICP-MS) experiments have uncovered a relationship between the subcellular distribution of these metalloinsertors and their biological activities. Specifically, we find that all of our metalloinsertors localize in the nucleus at sufficient concentrations for binding to DNA mismatches. However, the metalloinsertors with high rhodium localization in the mitochondria show toxicity that is not selective for MMR-deficient cells, whereas metalloinsertors with less mitochondrial rhodium show activity that is highly selective for MMR-deficient versus proficient cells. This work supports the notion that specific targeting of the metalloinsertors to nuclear DNA gives rise to their cell-selective cytotoxic and antiproliferative activities. The selectivity in cellular targeting depends upon binding to mismatches in genomic DNA. PMID:23137296

  9. Measurement Frontiers in Molecular Biology

    Science.gov (United States)

    Laderman, Stephen

    2009-03-01

    Developments of molecular measurements and manipulations have long enabled forefront research in evolution, genetics, biological development and its dysfunction, and the impact of external factors on the behavior of cells. Measurement remains at the heart of exciting and challenging basic and applied problems in molecular and cell biology. Methods to precisely determine the identity and abundance of particular molecules amongst a complex mixture of similar and dissimilar types require the successful design and integration of multiple steps involving biochemical manipulations, separations, physical probing, and data processing. Accordingly, today's most powerful methods for characterizing life at the molecular level depend on coordinated advances in applied physics, biochemistry, chemistry, computer science, and engineering. This is well illustrated by recent approaches to the measurement of DNA, RNA, proteins, and intact cells. Such successes underlie well founded visions of how molecular biology can further assist in answering compelling scientific questions and in enabling the development of remarkable advances in human health. These visions, in turn, are motivating the interdisciplinary creation of even more comprehensive measurements. As a further and closely related consequence, they are motivating innovations in the conceptual and practical approaches to organizing and visualizing large, complex sets of interrelated experimental results and distilling from those data compelling, informative conclusions.

  10. Expanding the chemical palate of cells by combining systems biology and metabolic engineering.

    Science.gov (United States)

    Curran, Kathleen A; Alper, Hal S

    2012-07-01

    The field of Metabolic Engineering has recently undergone a transformation that has led to a rapid expansion of the chemical palate of cells. Now, it is conceivable to produce nearly any organic molecule of interest using a cellular host. Significant advances have been made in the production of biofuels, biopolymers and precursors, pharmaceuticals and nutraceuticals, and commodity and specialty chemicals. Much of this rapid expansion in the field has been, in part, due to synergies and advances in the area of systems biology. Specifically, the availability of functional genomics, metabolomics and transcriptomics data has resulted in the potential to produce a wealth of new products, both natural and non-natural, in cellular factories. The sheer amount and diversity of this data however, means that uncovering and unlocking novel chemistries and insights is a non-obvious exercise. To address this issue, a number of computational tools and experimental approaches have been developed to help expedite the design process to create new cellular factories. This review will highlight many of the systems biology enabling technologies that have reduced the design cycle for engineered hosts, highlight major advances in the expanded diversity of products that can be synthesized, and conclude with future prospects in the field of metabolic engineering. Copyright © 2012 Elsevier Inc. All rights reserved.

  11. Multilayer microfluidic systems with indium-tin-oxide microelectrodes for studying biological cells

    International Nuclear Information System (INIS)

    Wu, Hsiang-Chiu; Chen, Hsin; Lyau, Jia-Bo; Lin, Min-Hsuan; Chuang, Yung-Jen

    2017-01-01

    Contemporary semiconductor and micromachining technologies have been exploited to develop lab-on-a-chip microsystems, which enable parallel and efficient experiments in molecular and cellular biology. In these microlab systems, microfluidics play an important role for automatic transportation or immobilization of cells and bio-molecules, as well as for separation or mixing of different chemical reagents. However, seldom microlab systems allow both morphology and electrophysiology of biological cells to be studied in situ . This kind of study is important, for example, for understanding how neuronal networks grow in response to environmental stimuli. To fulfill this application need, this paper investigates the possibility of fabricating multi-layer photoresists as microfluidic systems directly above a glass substrate with indium-tin-oxide (ITO) electrodes. The microfluidic channels are designed to guide and trap biological cells on top of ITO electrodes, through which the electrical activities of cells can be recorded or elicited. As both the microfluidic system and ITO electrodes are transparent, the cellular morphology is observable easily during electrophysiological studies. Two fabrication processes are proposed and compared. One defines the structure and curing depth of each photoresist layer simply by controlling the exposure time in lithography, while the other further utilizes a sacrificial layer to defines the structure of the bottom layer. The fabricated microfluidic system is proved bio-compatible and able to trap blood cells or neurons. Therefore, the proposed microsystem will be useful for studying cultured cells efficiently in applications such as drug-screening. (paper)

  12. SBR-Blood: systems biology repository for hematopoietic cells.

    Science.gov (United States)

    Lichtenberg, Jens; Heuston, Elisabeth F; Mishra, Tejaswini; Keller, Cheryl A; Hardison, Ross C; Bodine, David M

    2016-01-04

    Extensive research into hematopoiesis (the development of blood cells) over several decades has generated large sets of expression and epigenetic profiles in multiple human and mouse blood cell types. However, there is no single location to analyze how gene regulatory processes lead to different mature blood cells. We have developed a new database framework called hematopoietic Systems Biology Repository (SBR-Blood), available online at http://sbrblood.nhgri.nih.gov, which allows user-initiated analyses for cell type correlations or gene-specific behavior during differentiation using publicly available datasets for array- and sequencing-based platforms from mouse hematopoietic cells. SBR-Blood organizes information by both cell identity and by hematopoietic lineage. The validity and usability of SBR-Blood has been established through the reproduction of workflows relevant to expression data, DNA methylation, histone modifications and transcription factor occupancy profiles. Published by Oxford University Press on behalf of Nucleic Acids Research 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  13. Cell and molecular biology of the spiny dogfish Squalus acanthias and little skate Leucoraja erinacea: insights from in vitro cultured cells.

    Science.gov (United States)

    Barnes, D W

    2012-04-01

    Two of the most commonly used elasmobranch experimental model species are the spiny dogfish Squalus acanthias and the little skate Leucoraja erinacea. Comparative biology and genomics with these species have provided useful information in physiology, pharmacology, toxicology, immunology, evolutionary developmental biology and genetics. A wealth of information has been obtained using in vitro approaches to study isolated cells and tissues from these organisms under circumstances in which the extracellular environment can be controlled. In addition to classical work with primary cell cultures, continuously proliferating cell lines have been derived recently, representing the first cell lines from cartilaginous fishes. These lines have proved to be valuable tools with which to explore functional genomic and biological questions and to test hypotheses at the molecular level. In genomic experiments, complementary (c)DNA libraries have been constructed, and c. 8000 unique transcripts identified, with over 3000 representing previously unknown gene sequences. A sub-set of messenger (m)RNAs has been detected for which the 3' untranslated regions show elements that are remarkably well conserved evolutionarily, representing novel, potentially regulatory gene sequences. The cell culture systems provide physiologically valid tools to study functional roles of these sequences and other aspects of elasmobranch molecular cell biology and physiology. Information derived from the use of in vitro cell cultures is valuable in revealing gene diversity and information for genomic sequence assembly, as well as for identification of new genes and molecular markers, construction of gene-array probes and acquisition of full-length cDNA sequences. © 2012 The Author. Journal of Fish Biology © 2012 The Fisheries Society of the British Isles.

  14. Plasma membrane--cortical cytoskeleton interactions: a cell biology approach with biophysical considerations.

    Science.gov (United States)

    Kapus, András; Janmey, Paul

    2013-07-01

    From a biophysical standpoint, the interface between the cell membrane and the cytoskeleton is an intriguing site where a "two-dimensional fluid" interacts with an exceedingly complex three-dimensional protein meshwork. The membrane is a key regulator of the cytoskeleton, which not only provides docking sites for cytoskeletal elements through transmembrane proteins, lipid binding-based, and electrostatic interactions, but also serves as the source of the signaling events and molecules that control cytoskeletal organization and remolding. Conversely, the cytoskeleton is a key determinant of the biophysical and biochemical properties of the membrane, including its shape, tension, movement, composition, as well as the mobility, partitioning, and recycling of its constituents. From a cell biological standpoint, the membrane-cytoskeleton interplay underlies--as a central executor and/or regulator--a multitude of complex processes including chemical and mechanical signal transduction, motility/migration, endo-/exo-/phagocytosis, and other forms of membrane traffic, cell-cell, and cell-matrix adhesion. The aim of this article is to provide an overview of the tight structural and functional coupling between the membrane and the cytoskeleton. As biophysical approaches, both theoretical and experimental, proved to be instrumental for our understanding of the membrane/cytoskeleton interplay, this review will "oscillate" between the cell biological phenomena and the corresponding biophysical principles and considerations. After describing the types of connections between the membrane and the cytoskeleton, we will focus on a few key physical parameters and processes (force generation, curvature, tension, and surface charge) and will discuss how these contribute to a variety of fundamental cell biological functions. © 2013 American Physiological Society.

  15. Systems Modelling and the Development of Coherent Understanding of Cell Biology

    Science.gov (United States)

    Verhoeff, Roald P.; Waarlo, Arend Jan; Boersma, Kerst Th.

    2008-01-01

    This article reports on educational design research concerning a learning and teaching strategy for cell biology in upper-secondary education introducing "systems modelling" as a key competence. The strategy consists of four modelling phases in which students subsequently develop models of free-living cells, a general two-dimensional model of…

  16. More Ideas for Monitoring Biological Experiments with the BBC Computer: Absorption Spectra, Yeast Growth, Enzyme Reactions and Animal Behaviour.

    Science.gov (United States)

    Openshaw, Peter

    1988-01-01

    Presented are five ideas for A-level biology experiments using a laboratory computer interface. Topics investigated include photosynthesis, yeast growth, animal movements, pulse rates, and oxygen consumption and production by organisms. Includes instructions specific to the BBC computer system. (CW)

  17. N-Cadherin Maintains the Healthy Biology of Nucleus Pulposus Cells under High-Magnitude Compression.

    Science.gov (United States)

    Wang, Zhenyu; Leng, Jiali; Zhao, Yuguang; Yu, Dehai; Xu, Feng; Song, Qingxu; Qu, Zhigang; Zhuang, Xinming; Liu, Yi

    2017-01-01

    Mechanical load can regulate disc nucleus pulposus (NP) biology in terms of cell viability, matrix homeostasis and cell phenotype. N-cadherin (N-CDH) is a molecular marker of NP cells. This study investigated the role of N-CDH in maintaining NP cell phenotype, NP matrix synthesis and NP cell viability under high-magnitude compression. Rat NP cells seeded on scaffolds were perfusion-cultured using a self-developed perfusion bioreactor for 5 days. NP cell biology in terms of cell apoptosis, matrix biosynthesis and cell phenotype was studied after the cells were subjected to different compressive magnitudes (low- and high-magnitudes: 2% and 20% compressive deformation, respectively). Non-loaded NP cells were used as controls. Lentivirus-mediated N-CDH overexpression was used to further investigate the role of N-CDH under high-magnitude compression. The 20% deformation compression condition significantly decreased N-CDH expression compared with the 2% deformation compression and control conditions. Meanwhile, 20% deformation compression increased the number of apoptotic NP cells, up-regulated the expression of Bax and cleaved-caspase-3 and down-regulated the expression of Bcl-2, matrix macromolecules (aggrecan and collagen II) and NP cell markers (glypican-3, CAXII and keratin-19) compared with 2% deformation compression. Additionally, N-CDH overexpression attenuated the effects of 20% deformation compression on NP cell biology in relation to the designated parameters. N-CDH helps to restore the cell viability, matrix biosynthesis and cellular phenotype of NP cells under high-magnitude compression. © 2017 The Author(s). Published by S. Karger AG, Basel.

  18. Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models.

    Science.gov (United States)

    Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J

    2014-01-01

    The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. © 2014 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.

  19. Perception analysis of undergraduate students in the health field about the topic Cell Biology

    Directory of Open Access Journals (Sweden)

    Carlos Alberto Andrade Monerat

    2015-06-01

    Full Text Available The Brazilian education has been changing over time, especially with the increased offer on the various levels of education. In undergraduate courses, in the health area, the cell biology becomes an essential discipline, because various sectors are directly influenced by their recent discoveries and research. This work aimed to analyze, with undergraduate students, perceptions about the themes at Cell Biology, revealing, with its results, pertinent aspects, as insufficient knowledge about the proposed theme. The definition of a concept of cell, considered a basic aspect, however relevant in this context, exemplifies this situation, because it showed a considerable rate of unsatisfactory answers. On the other hand, was verified the recognition of Cell Biology as an area that presents important contents in the training of these students, due the numerous scientific researches that show its constant evolution in association with themes of medicine and public health.

  20. Systems Biology of the Fluxome

    Directory of Open Access Journals (Sweden)

    Miguel A. Aon

    2015-07-01

    Full Text Available The advent of high throughput -omics has made the accumulation of comprehensive data sets possible, consisting of changes in genes, transcripts, proteins and metabolites. Systems biology-inspired computational methods for translating metabolomics data into fluxomics provide a direct functional, dynamic readout of metabolic networks. When combined with appropriate experimental design, these methods deliver insightful knowledge about cellular function under diverse conditions. The use of computational models accounting for detailed kinetics and regulatory mechanisms allow us to unravel the control and regulatory properties of the fluxome under steady and time-dependent behaviors. This approach extends the analysis of complex systems from description to prediction, including control of complex dynamic behavior ranging from biological rhythms to catastrophic lethal arrhythmias. The powerful quantitative metabolomics-fluxomics approach will help our ability to engineer unicellular and multicellular organisms evolve from trial-and-error to a more predictable process, and from cells to organ and organisms.

  1. Multiweek Cell Culture Project for Use in Upper-Level Biology Laboratories

    Science.gov (United States)

    Marion, Rebecca E.; Gardner, Grant E.; Parks, Lisa D.

    2012-01-01

    This article describes a laboratory protocol for a multiweek project piloted in a new upper-level biology laboratory (BIO 426) using cell culture techniques. Human embryonic kidney-293 cells were used, and several culture media and supplements were identified for students to design their own experiments. Treatments included amino acids, EGF,…

  2. Chimeric animal models in human stem cell biology.

    Science.gov (United States)

    Glover, Joel C; Boulland, Jean-Luc; Halasi, Gabor; Kasumacic, Nedim

    2009-01-01

    The clinical use of stem cells for regenerative medicine is critically dependent on preclinical studies in animal models. In this review we examine some of the key issues and challenges in the use of animal models to study human stem cell biology-experimental standardization, body size, immunological barriers, cell survival factors, fusion of host and donor cells, and in vivo imaging and tracking. We focus particular attention on the various imaging modalities that can be used to track cells in living animals, comparing their strengths and weaknesses and describing technical developments that are likely to lead to new opportunities for the dynamic assessment of stem cell behavior in vivo. We then provide an overview of some of the most commonly used animal models, their advantages and disadvantages, and examples of their use for xenotypic transplantation of human stem cells, with separate reviews of models involving rodents, ungulates, nonhuman primates, and the chicken embryo. As the use of human somatic, embryonic, and induced pluripotent stem cells increases, so too will the range of applications for these animal models. It is likely that increasingly sophisticated uses of human/animal chimeric models will be developed through advances in genetic manipulation, cell delivery, and in vivo imaging.

  3. Chemotherapy curable malignancies and cancer stem cells: a biological review and hypothesis.

    Science.gov (United States)

    Savage, Philip

    2016-11-21

    Cytotoxic chemotherapy brings routine cures to only a small select group of metastatic malignancies comprising gestational trophoblast tumours, germ cell tumours, acute leukemia, Hodgkin's disease, high grade lymphomas and some of the rare childhood malignancies. We have previously postulated that the extreme sensitivity to chemotherapy for these malignancies is linked to the on-going high levels of apoptotic sensitivity that is naturally linked with the unique genetic events of nuclear fusion, meiosis, VDJ recombination, somatic hypermutation, and gastrulation that have occurred within the cells of origin of these malignancies. In this review we will examine the cancer stem cell/cancer cell relationship of each of the chemotherapy curable malignancies and how this relationship impacts on the resultant biology and pro-apoptotic sensitivity of the varying cancer cell types. In contrast to the common epithelial cancers, in each of the chemotherapy curable malignancies there are no conventional hierarchical cancer stem cells. However cells with cancer stem like qualities can arise stochastically from within the general tumour cell population. These stochastic stem cells acquire a degree of resistance to DNA damaging agents but also retain much of the key characteristics of the cancer cells from which they develop. We would argue that the balance between the acquired resistance of the stochastic cancer stem cell and the inherent chemotherapy sensitivity of parent tumour cell determines the overall chemotherapy curability of each diagnosis. The cancer stem cells in the chemotherapy curable malignancies appear to have two key biological differences from those of the more common chemotherapy incurable malignancies. The first difference is that the conventional hierarchical pattern of cancer stem cells is absent in each of the chemotherapy curable malignancies. The other key difference, we suggest, is that the stochastic stem cells in the chemotherapy curable malignancies

  4. Computation: A New Open Access Journal of Computational Chemistry, Computational Biology and Computational Engineering

    OpenAIRE

    Karlheinz Schwarz; Rainer Breitling; Christian Allen

    2013-01-01

    Computation (ISSN 2079-3197; http://www.mdpi.com/journal/computation) is an international scientific open access journal focusing on fundamental work in the field of computational science and engineering. Computational science has become essential in many research areas by contributing to solving complex problems in fundamental science all the way to engineering. The very broad range of application domains suggests structuring this journal into three sections, which are briefly characterized ...

  5. Lessons learned about spaceflight and cell biology experiments

    Science.gov (United States)

    Hughes-Fulford, Millie

    2004-01-01

    Conducting cell biology experiments in microgravity can be among the most technically challenging events in a biologist's life. Conflicting events of spaceflight include waiting to get manifested, delays in manifest schedules, training astronauts to not shake your cultures and to add reagents slowly, as shaking or quick injection can activate signaling cascades and give you erroneous results. It is important to select good hardware that is reliable. Possible conflicting environments in flight include g-force and vibration of launch, exposure of cells to microgravity for extended periods until hardware is turned on, changes in cabin gases and cosmic radiation. One should have an on-board 1-g control centrifuge in order to eliminate environmental differences. Other obstacles include getting your funding in a timely manner (it is not uncommon for two to three years to pass between notification of grant approval for funding and actually getting funded). That said, it is important to note that microgravity research is worthwhile since all terrestrial life evolved in a gravity field and secrets of biological function may only be answered by removing the constant of gravity. Finally, spaceflight experiments are rewarding and worth your effort and patience.

  6. Multiweek cell culture project for use in upper-level biology laboratories.

    Science.gov (United States)

    Marion, Rebecca E; Gardner, Grant E; Parks, Lisa D

    2012-06-01

    This article describes a laboratory protocol for a multiweek project piloted in a new upper-level biology laboratory (BIO 426) using cell culture techniques. Human embryonic kidney-293 cells were used, and several culture media and supplements were identified for students to design their own experiments. Treatments included amino acids, EGF, caffeine, epinephrine, heavy metals, and FBS. Students researched primary literature to determine their experimental variables, made their own solutions, and treated their cells over a period of 2 wk. Before this, a sterile technique laboratory was developed to teach students how to work with the cells and minimize contamination. Students designed their experiments, mixed their solutions, seeded their cells, and treated them with their control and experimental media. Students had the choice of manipulating a number of variables, including incubation times, exposure to treatment media, and temperature. At the end of the experiment, students observed the effects of their treatment, harvested and dyed their cells, counted relative cell numbers in control and treatment flasks, and determined the ratio of living to dead cells using a hemocytometer. At the conclusion of the experiment, students presented their findings in a poster presentation. This laboratory can be expanded or adapted to include additional cell lines and treatments. The ability to design and implement their own experiments has been shown to increase student engagement in the biology-related laboratory activities as well as develop the critical thinking skills needed for independent research.

  7. Engineered Breast Cancer Cell Spheroids Reproduce Biologic Properties of Solid Tumors.

    Science.gov (United States)

    Ham, Stephanie L; Joshi, Ramila; Luker, Gary D; Tavana, Hossein

    2016-11-01

    Solid tumors develop as 3D tissue constructs. As tumors grow larger, spatial gradients of nutrients and oxygen and inadequate diffusive supply to cells distant from vasculature develops. Hypoxia initiates signaling and transcriptional alterations to promote survival of cancer cells and generation of cancer stem cells (CSCs) that have self-renewal and tumor-initiation capabilities. Both hypoxia and CSCs are associated with resistance to therapies and tumor relapse. This study demonstrates that 3D cancer cell models, known as tumor spheroids, generated with a polymeric aqueous two-phase system (ATPS) technology capture these important biological processes. Similar to solid tumors, spheroids of triple negative breast cancer cells deposit major extracellular matrix proteins. The molecular analysis establishes presence of hypoxic cells in the core region and expression of CSC gene and protein markers including CD24, CD133, and Nanog. Importantly, these spheroids resist treatment with chemotherapy drugs. A combination treatment approach using a hypoxia-activated prodrug, TH-302, and a chemotherapy drug, doxorubicin, successfully targets drug resistant spheroids. This study demonstrates that ATPS spheroids recapitulate important biological and functional properties of solid tumors and provide a unique model for studies in cancer research. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Of mice and women: a comparative tissue biology perspective of breast stem cells and differentiation.

    Science.gov (United States)

    Dontu, Gabriela; Ince, Tan A

    2015-06-01

    Tissue based research requires a background in human and veterinary pathology, developmental biology, anatomy, as well as molecular and cellular biology. This type of comparative tissue biology (CTB) expertise is necessary to tackle some of the conceptual challenges in human breast stem cell research. It is our opinion that the scarcity of CTB expertise contributed to some erroneous interpretations in tissue based research, some of which are reviewed here in the context of breast stem cells. In this article we examine the dissimilarities between mouse and human mammary tissue and suggest how these may impact stem cell studies. In addition, we consider the differences between breast ducts vs. lobules and clarify how these affect the interpretation of results in stem cell research. Lastly, we introduce a new elaboration of normal epithelial cell types in human breast and discuss how this provides a clinically useful basis for breast cancer classification.

  9. Ovary and fimbrial stem cells: biology, niche and cancer origins.

    Science.gov (United States)

    Ng, Annie; Barker, Nick

    2015-10-01

    The mammalian ovary is covered by a single-layered epithelium that undergoes rupture and remodelling following each ovulation. Although resident stem cells are presumed to be crucial for this cyclic regeneration, their identity and mode of action have been elusive. Surrogate stemness assays and in vivo fate-mapping studies using recently discovered stem cell markers have identified stem cell pools in the ovary and fimbria that ensure epithelial homeostasis. Recent findings provide insights into intrinsic mechanisms and local extrinsic cues that govern the function of ovarian and fimbrial stem cells. These discoveries have advanced our understanding of stem cell biology in the ovary and fimbria, and lay the foundations for evaluating the contribution of resident stem cells to the initiation and progression of human epithelial ovarian cancer.

  10. Cell Biology of Astrocyte-Synapse Interactions.

    Science.gov (United States)

    Allen, Nicola J; Eroglu, Cagla

    2017-11-01

    Astrocytes, the most abundant glial cells in the mammalian brain, are critical regulators of brain development and physiology through dynamic and often bidirectional interactions with neuronal synapses. Despite the clear importance of astrocytes for the establishment and maintenance of proper synaptic connectivity, our understanding of their role in brain function is still in its infancy. We propose that this is at least in part due to large gaps in our knowledge of the cell biology of astrocytes and the mechanisms they use to interact with synapses. In this review, we summarize some of the seminal findings that yield important insight into the cellular and molecular basis of astrocyte-neuron communication, focusing on the role of astrocytes in the development and remodeling of synapses. Furthermore, we pose some pressing questions that need to be addressed to advance our mechanistic understanding of the role of astrocytes in regulating synaptic development. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Synthetic biology expands chemical control of microorganisms.

    Science.gov (United States)

    Ford, Tyler J; Silver, Pamela A

    2015-10-01

    The tools of synthetic biology allow researchers to change the ways engineered organisms respond to chemical stimuli. Decades of basic biology research and new efforts in computational protein and RNA design have led to the development of small molecule sensors that can be used to alter organism function. These new functions leap beyond the natural propensities of the engineered organisms. They can range from simple fluorescence or growth reporting to pathogen killing, and can involve metabolic coordination among multiple cells or organisms. Herein, we discuss how synthetic biology alters microorganisms' responses to chemical stimuli resulting in the development of microbes as toxicity sensors, disease treatments, and chemical factories. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. At the cutting edge: applications and perspectives of laser nanosurgery in cell biology.

    Science.gov (United States)

    Ronchi, Paolo; Terjung, Stefan; Pepperkok, Rainer

    2012-04-01

    Laser-mediated nanosurgery has become popular in the last decade because of the previously unexplored possibility of ablating biological material inside living cells with sub-micrometer precision. A number of publications have shown the potential applications of this technique, ranging from the dissection of sub-cellular structures to surgical ablations of whole cells or tissues in model systems such as Drosophila melanogaster or Danio rerio . In parallel, the recent development of micropatterning techniques has given cell biologists the possibility to shape cells and reproducibly organize the intracellular space. The integration of these two techniques has only recently started yet their combination has proven to be very interesting. The aim of this review is to present recent applications of laser nanosurgery in cell biology and to discuss the possible developments of this approach, particularly in combination with micropattern-mediated endomembrane organization.

  13. Phase-contrast x-ray computed tomography for biological imaging

    Science.gov (United States)

    Momose, Atsushi; Takeda, Tohoru; Itai, Yuji

    1997-10-01

    We have shown so far that 3D structures in biological sot tissues such as cancer can be revealed by phase-contrast x- ray computed tomography using an x-ray interferometer. As a next step, we aim at applications of this technique to in vivo observation, including radiographic applications. For this purpose, the size of view field is desired to be more than a few centimeters. Therefore, a larger x-ray interferometer should be used with x-rays of higher energy. We have evaluated the optimal x-ray energy from an aspect of does as a function of sample size. Moreover, desired spatial resolution to an image sensor is discussed as functions of x-ray energy and sample size, basing on a requirement in the analysis of interference fringes.

  14. A direct method for computing extreme value (Gumbel) parameters for gapped biological sequence alignments.

    Science.gov (United States)

    Quinn, Terrance; Sinkala, Zachariah

    2014-01-01

    We develop a general method for computing extreme value distribution (Gumbel, 1958) parameters for gapped alignments. Our approach uses mixture distribution theory to obtain associated BLOSUM matrices for gapped alignments, which in turn are used for determining significance of gapped alignment scores for pairs of biological sequences. We compare our results with parameters already obtained in the literature.

  15. Synthesis and biological evaluation of the progenitor of a new class of cephalosporin analogues, with a particular focus on structure-based computational analysis.

    Directory of Open Access Journals (Sweden)

    Anna Verdino

    Full Text Available We present the synthesis and biological evaluation of the prototype of a new class of cephalosporins, containing an additional isolated beta lactam ring with two phenyl substituents. This new compound is effective against Gram positive microorganisms, with a potency similar to that of ceftriaxone, a cephalosporin widely used in clinics and taken as a reference, and with no cytotoxicity against two different human cell lines, even at a concentration much higher than the minimal inhibitory concentration tested. Additionally, a deep computational analysis has been conducted with the aim of understanding the contribution of its moieties to the binding energy towards several penicillin-binding proteins from both Gram positive and Gram negative bacteria. All these results will help us developing derivatives of this compound with improved chemical and biological properties, such as a broader spectrum of action and/or an increased affinity towards their molecular targets.

  16. Novel insights into embryonic stem cell self-renewal revealed through comparative human and mouse systems biology networks.

    Science.gov (United States)

    Dowell, Karen G; Simons, Allen K; Bai, Hao; Kell, Braden; Wang, Zack Z; Yun, Kyuson; Hibbs, Matthew A

    2014-05-01

    Embryonic stem cells (ESCs), characterized by their ability to both self-renew and differentiate into multiple cell lineages, are a powerful model for biomedical research and developmental biology. Human and mouse ESCs share many features, yet have distinctive aspects, including fundamental differences in the signaling pathways and cell cycle controls that support self-renewal. Here, we explore the molecular basis of human ESC self-renewal using Bayesian network machine learning to integrate cell-type-specific, high-throughput data for gene function discovery. We integrated high-throughput ESC data from 83 human studies (~1.8 million data points collected under 1,100 conditions) and 62 mouse studies (~2.4 million data points collected under 1,085 conditions) into separate human and mouse predictive networks focused on ESC self-renewal to analyze shared and distinct functional relationships among protein-coding gene orthologs. Computational evaluations show that these networks are highly accurate, literature validation confirms their biological relevance, and reverse transcriptase polymerase chain reaction (RT-PCR) validation supports our predictions. Our results reflect the importance of key regulatory genes known to be strongly associated with self-renewal and pluripotency in both species (e.g., POU5F1, SOX2, and NANOG), identify metabolic differences between species (e.g., threonine metabolism), clarify differences between human and mouse ESC developmental signaling pathways (e.g., leukemia inhibitory factor (LIF)-activated JAK/STAT in mouse; NODAL/ACTIVIN-A-activated fibroblast growth factor in human), and reveal many novel genes and pathways predicted to be functionally associated with self-renewal in each species. These interactive networks are available online at www.StemSight.org for stem cell researchers to develop new hypotheses, discover potential mechanisms involving sparsely annotated genes, and prioritize genes of interest for experimental validation

  17. Glucose Transport in Cultured Animal Cells: An Exercise for the Undergraduate Cell Biology Laboratory

    Science.gov (United States)

    Ledbetter, Mary Lee S.; Lippert, Malcolm J.

    2002-01-01

    Membrane transport is a fundamental concept that undergraduate students of cell biology understand better with laboratory experience. Formal teaching exercises commonly used to illustrate this concept are unbiological, qualitative, or intricate and time consuming to prepare. We have developed an exercise that uses uptake of radiolabeled nutrient…

  18. Next Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology (Final Report)

    Science.gov (United States)

    EPA announced the release of the final report, Next Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology. This report describes new approaches that are faster, less resource intensive, and more robust that can help ...

  19. Biological and Environmental Research Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Biological and Environmental Research, March 28-31, 2016, Rockville, Maryland

    Energy Technology Data Exchange (ETDEWEB)

    Arkin, Adam [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bader, David C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Coffey, Richard [Argonne National Lab. (ANL), Argonne, IL (United States); Antypas, Katie [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bard, Deborah [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Dart, Eli [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Esnet; Dosanjh, Sudip [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Gerber, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hack, James [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Monga, Inder [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Esnet; Papka, Michael E. [Argonne National Lab. (ANL), Argonne, IL (United States); Riley, Katherine [Argonne National Lab. (ANL), Argonne, IL (United States); Rotman, Lauren [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Esnet; Straatsma, Tjerk [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wells, Jack [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Aluru, Srinivas [Georgia Inst. of Technology, Atlanta, GA (United States); Andersen, Amity [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Aprá, Edoardo [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). EMSL; Azad, Ariful [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bates, Susan [National Center for Atmospheric Research, Boulder, CO (United States); Blaby, Ian [Brookhaven National Lab. (BNL), Upton, NY (United States); Blaby-Haas, Crysten [Brookhaven National Lab. (BNL), Upton, NY (United States); Bonneau, Rich [New York Univ. (NYU), NY (United States); Bowen, Ben [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bradford, Mark A. [Yale Univ., New Haven, CT (United States); Brodie, Eoin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Brown, James (Ben) [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Buluc, Aydin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bernholdt, David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Bylaska, Eric [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Calvin, Kate [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Cannon, Bill [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Chen, Xingyuan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Cheng, Xiaolin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cheung, Margaret [Univ. of Houston, Houston, TX (United States); Chowdhary, Kenny [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Colella, Phillip [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Collins, Bill [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Compo, Gil [National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States); Crowley, Mike [National Renewable Energy Lab. (NREL), Golden, CO (United States); Debusschere, Bert [Sandia National Lab. (SNL-CA), Livermore, CA (United States); D’Imperio, Nicholas [Brookhaven National Lab. (BNL), Upton, NY (United States); Dror, Ron [Stanford Univ., Stanford, CA (United States); Egan, Rob [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Evans, Katherine [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Friedberg, Iddo [Iowa State Univ., Ames, IA (United States); Fyke, Jeremy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Gao, Zheng [Stony Brook Univ., Stony Brook, NY (United States); Georganas, Evangelos [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Giraldo, Frank [Naval Postgraduate School, Monterey, CA (United States); Gnanakaran, Gnana [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Govind, Niri [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). EMSL; Grandy, Stuart [Univ. of New Hampshire, Durham, NH (United States); Gustafson, Bill [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hammond, Glenn [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hargrove, William [USDA Forest Service, Washington, D.C. (United States); Heroux, Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hoffman, Forrest [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hofmeyr, Steven [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hunke, Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Jackson, Charles [Univ. of Texas-Austin, Austin, TX (United States); Jacob, Rob [Argonne National Lab. (ANL), Argonne, IL (United States); Jacobson, Dan [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Jacobson, Matt [Univ. of California, San Francisco, CA (United States); Jain, Chirag [Georgia Inst. of Technology, Atlanta, GA (United States); Johansen, Hans [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Johnson, Jeff [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jones, Andy [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jones, Phil [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Kalyanaraman, Ananth [Washington State Univ., Pullman, WA (United States); Kang, Senghwa [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); King, Eric [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Koanantakool, Penporn [Univ. of California, Berkeley, CA (United States); Kollias, Pavlos [Stony Brook Univ., Stony Brook, NY (United States); Kopera, Michal [Univ. of California, Santa Cruz, CA (United States); Kotamarthi, Rao [Argonne National Lab. (ANL), Argonne, IL (United States); Kowalski, Karol [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). EMSL; Kumar, Jitendra [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kyrpides, Nikos [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Leung, Ruby [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Li, Xiaolin [Stony Brook Univ., Stony Brook, NY (United States); Lin, Wuyin [Brookhaven National Lab. (BNL), Upton, NY (United States); Link, Robert [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Liu, Yangang [Brookhaven National Lab. (BNL), Upton, NY (United States); Loew, Leslie [Univ. of Connecticut, Storrs, CT (United States); Luke, Edward [Brookhaven National Lab. (BNL), Upton, NY (United States); Ma, Hsi -Yen [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Mahadevan, Radhakrishnan [Univ. of Toronto, Toronto, ON (Canada); Maranas, Costas [Pennsylvania State Univ., University Park, PA (United States); Martin, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States); McCue, Lee Ann [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); McInnes, Lois Curfman [Argonne National Lab. (ANL), Argonne, IL (United States); Mills, Richard [Intel Corp., Santa Clara, CA (United States); Molins Rafa, Sergi [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Morozov, Dmitriy [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Mostafavi, Sara [Center for Molecular Medicine and Therapeutics, Vancouver, BC (Canada); Moulton, David J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Mourao, Zenaida [Univ. of Cambridge (United Kingdom); Najm, Habib [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Ng, Bernard [Center for Molecular Medicine and Therapeutics, Vancouver, BC (Canada); Ng, Esmond [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Norman, Matt [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Oh, Sang -Yun [Univ. of California, Santa Barbara, CA (United States); Oliker, Leonid [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Pan, Chongle [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Pass, Rebecca [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Pau, George S. H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Petridis, Loukas [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Prakash, Giri [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Price, Stephen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Randall, David [Colorado State Univ., Fort Collins, CO (United States); Renslow, Ryan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Riihimaki, Laura [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Ringler, Todd [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Roberts, Andrew [Naval Postgraduate School, Monterey, CA (United States); Rokhsar, Dan [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ruebel, Oliver [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Salinger, Andrew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Scheibe, Tim [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Schulz, Roland [Intel, Mountain View, CA (United States); Sivaraman, Chitra [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Smith, Jeremy [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Sreepathi, Sarat [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Steefel, Carl [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Talbot, Jenifer [Boston Univ., Boston, MA (United States); Tantillo, D. J. [Univ. of California, Davis, CA (United States); Tartakovsky, Alex [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Taylor, Mark [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Taylor, Ronald [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Trebotich, David [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Urban, Nathan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Valiev, Marat [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). EMSL; Wagner, Allon [Univ. of California, Berkeley, CA (United States); Wainwright, Haruko [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wieder, Will [NCAR/Univ. of Colorado, Boulder, CO (United States); Wiley, Steven [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Williams, Dean [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Worley, Pat [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Xie, Shaocheng [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Yelick, Kathy [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Yoo, Shinjae [Brookhaven National Lab. (BNL), Upton, NY (United States); Yosef, Niri [Univ. of California, Berkeley, CA (United States); Zhang, Minghua [Stony Brook Univ., Stony Brook, NY (United States)

    2016-03-31

    Understanding the fundamentals of genomic systems or the processes governing impactful weather patterns are examples of the types of simulation and modeling performed on the most advanced computing resources in America. High-performance computing and computational science together provide a necessary platform for the mission science conducted by the Biological and Environmental Research (BER) office at the U.S. Department of Energy (DOE). This report reviews BER’s computing needs and their importance for solving some of the toughest problems in BER’s portfolio. BER’s impact on science has been transformative. Mapping the human genome, including the U.S.-supported international Human Genome Project that DOE began in 1987, initiated the era of modern biotechnology and genomics-based systems biology. And since the 1950s, BER has been a core contributor to atmospheric, environmental, and climate science research, beginning with atmospheric circulation studies that were the forerunners of modern Earth system models (ESMs) and by pioneering the implementation of climate codes onto high-performance computers. See http://exascaleage.org/ber/ for more information.

  20. From cell biology to immunology: Controlling metastatic progression of cancer via microRNA regulatory networks.

    Science.gov (United States)

    Park, Jae Hyon; Theodoratou, Evropi; Calin, George A; Shin, Jae Il

    2016-01-01

    Recently, the study of microRNAs has expanded our knowledge of the fundamental processes of cancer biology and the underlying mechanisms behind tumor metastasis. Extensive research in the fields of microRNA and its novel mechanisms of actions against various cancers has more recently led to the trial of a first cancer-targeted microRNA drug, MRX34. Yet, these microRNAs are mostly being studied and clinically trialed solely based on the understanding of their cell biologic effects, thus, neglecting the important immunologic effects that are sometimes opposite of the cell biologic effects. Here, we summarize both the cell biologic and immunologic effects of various microRNAs and discuss the importance of considering both effects before using them in clinical settings. We stress the importance of understanding the miRNA's effect on cancer metastasis from a "systems" perspective before developing a miRNA-targeted therapeutic in treating cancer metastasis.

  1. Non-Chemical Distant Cellular Interactions as a potential confounder of Cell Biology Experiments

    Directory of Open Access Journals (Sweden)

    Ashkan eFarhadi

    2014-10-01

    Full Text Available Distant cells can communicate with each other through a variety of methods. Two such methods involve electrical and/or chemical mechanisms. Non-chemical, distant cellular interactions may be another method of communication that cells can use to modify the behavior of other cells that are mechanically separated. Moreover, non-chemical, distant cellular interactions may explain some cases of confounding effects in Cell Biology experiments. In this article, we review non-chemical, distant cellular interactions studies to try to shed light on the mechanisms in this highly unconventional field of cell biology. Despite the existence of several theories that try to explain the mechanism of non-chemical, distant cellular interactions, this phenomenon is still speculative. Among candidate mechanisms, electromagnetic waves appear to have the most experimental support. In this brief article, we try to answer a few key questions that may further clarify this mechanism.

  2. The role of EMMPRIN in T cell biology and immunological diseases.

    Science.gov (United States)

    Hahn, Jennifer Nancy; Kaushik, Deepak Kumar; Yong, V Wee

    2015-07-01

    EMMPRIN (CD147), originally described as an inducer of the expression of MMPs, has gained attention in its involvement in various immunologic diseases, such that anti-EMMPRIN antibodies are considered as potential therapeutic medications. Given that MMPs are involved in the pathogenesis of various disease states, it is relevant that targeting an upstream inducer would make for an effective therapeutic strategy. Additionally, EMMPRIN is now appreciated to have multiple roles apart from MMP induction, including in cellular functions, such as migration, adhesion, invasion, energy metabolism, as well as T cell activation and proliferation. Here, we review what is known about EMMPRIN in numerous immunologic/inflammatory disease conditions with a particular focus on its complex roles in T cell biology. © Society for Leukocyte Biology.

  3. Inhibition of survivin influences the biological activities of canine histiocytic sarcoma cell lines.

    Directory of Open Access Journals (Sweden)

    Hiroki Yamazaki

    Full Text Available Canine histiocytic sarcoma (CHS is an aggressive malignant neoplasm that originates from histiocytic lineage cells, including dendritic cells and macrophages, and is characterized by progressive local infiltration and a very high metastatic potential. Survivin is as an apoptotic inhibitory factor that has major functions in cell proliferation, including inhibition of apoptosis and regulation of cell division, and is expressed in most types of human and canine malignant neoplasms, including melanoma and osteosarcoma. To investigate whether survivin was expressed at high levels in CHS and whether its expression was correlated with the aggressive biological behavior of CHS, we assessed relation between survivin expression and CHS progression, as well as the effects of survivin inhibition on the biological activities of CHS cells. We comparatively analyzed the expression of 6 selected anti-apoptotic genes, including survivin, in specimens from 30 dogs with histiocytic sarcoma and performed annexin V staining to evaluate apoptosis, methylthiazole tetrazolium assays to assess cell viability and chemosensitivity, and latex bead assays to measure changes in phagocytic activities in 4 CHS cell lines and normal canine fibroblasts transfected with survivin siRNA. Survivin gene expression levels in 30 specimens were significantly higher than those of the other 6 genes. After transfection with survivin siRNA, apoptosis, cell growth inhibition, enhanced chemosensitivity, and weakened phagocytic activities were observed in all CHS cell lines. In contrast, normal canine fibroblasts were not significantly affected by survivin knockdown. These results suggested that survivin expression may mediate the aggressive biological activities of CHS and that survivin may be an effective therapeutic target for the treatment of CHS.

  4. Primary culture of glial cells from mouse sympathetic cervical ganglion: a valuable tool for studying glial cell biology.

    Science.gov (United States)

    de Almeida-Leite, Camila Megale; Arantes, Rosa Maria Esteves

    2010-12-15

    Central nervous system glial cells as astrocytes and microglia have been investigated in vitro and many intracellular pathways have been clarified upon various stimuli. Peripheral glial cells, however, are not as deeply investigated in vitro despite its importance role in inflammatory and neurodegenerative diseases. Based on our previous experience of culturing neuronal cells, our objective was to standardize and morphologically characterize a primary culture of mouse superior cervical ganglion glial cells in order to obtain a useful tool to study peripheral glial cell biology. Superior cervical ganglia from neonatal C57BL6 mice were enzymatically and mechanically dissociated and cells were plated on diluted Matrigel coated wells in a final concentration of 10,000cells/well. Five to 8 days post plating, glial cell cultures were fixed for morphological and immunocytochemical characterization. Glial cells showed a flat and irregular shape, two or three long cytoplasm processes, and round, oval or long shaped nuclei, with regular outline. Cell proliferation and mitosis were detected both qualitative and quantitatively. Glial cells were able to maintain their phenotype in our culture model including immunoreactivity against glial cell marker GFAP. This is the first description of immunocytochemical characterization of mouse sympathetic cervical ganglion glial cells in primary culture. This work discusses the uses and limitations of our model as a tool to study many aspects of peripheral glial cell biology. Copyright © 2010 Elsevier B.V. All rights reserved.

  5. Biologic activities of recombinant human-beta-defensin-4 toward cultured human cancer cells.

    Science.gov (United States)

    Gerashchenko, O L; Zhuravel, E V; Skachkova, O V; Khranovska, N N; Filonenko, V V; Pogrebnoy, P V; Soldatkina, M A

    2013-06-01

    The aim of the study was in vitro analysis of biological activity of recombinant human beta-defensin-4 (rec-hBD-4). hBD-4 cDNA was cloned into pGEX-2T vector, and recombinant plasmid was transformed into E. coli BL21(DE3) cells. To purify soluble fusion GST-hBD-4 protein, affinity chromatography was applied. Rec-hBD-4 was cleaved from the fusion protein with thrombin, and purified by reverse phase chromatography on Sep-Pack C18. Effects of rec-hBD-4 on proliferation, viability, cell cycle distribution, substrate-independent growth, and mobility of cultured human cancer cells of A431, A549, and TPC-1 lines were analyzed by direct cell counting technique, MTT assay, flow cytofluorometry, colony forming assay in semi-soft medium, and wound healing assay. Rec-hBD-4 was expressed in bacterial cells as GST-hBD-4 fusion protein, and purified by routine 3-step procedure (affine chromatography on glutathione-agarose, cleavage of fusion protein by thrombin, and reverse phase chromatography). Analysis of in vitro activity of rec-hBD-4 toward three human cancer cell lines has demonstrated that the defensin is capable to affect cell behaviour in concentration-dependent manner. In 1-100 nM concentrations rec-hBD-4 significantly stimulates cancer cell proliferation and viability, and promotes cell cycle progression through G2/M checkpoint, greatly enhances colony-forming activity and mobility of the cells. Treatment of the cells with 500 nM of rec-hBD-4 resulted in opposite effects: significant suppression of cell proliferation and viability, blockage of cell cycle in G1/S checkpoint, significant inhibition of cell migration and colony forming activity. Recombinant human beta-defensin-4 is biologically active peptide capable to cause oppositely directed effects toward biologic features of cancer cells in vitro dependent on its concentration.

  6. Single cell biology beyond the era of antibodies: relevance, challenges, and promises in biomedical research.

    Science.gov (United States)

    Abraham, Parvin; Maliekal, Tessy Thomas

    2017-04-01

    Research of the past two decades has proved the relevance of single cell biology in basic research and translational medicine. Successful detection and isolation of specific subsets is the key to understand their functional heterogeneity. Antibodies are conventionally used for this purpose, but their relevance in certain contexts is limited. In this review, we discuss some of these contexts, posing bottle neck for different fields of biology including biomedical research. With the advancement of chemistry, several methods have been introduced to overcome these problems. Even though microfluidics and microraft array are newer techniques exploited for single cell biology, fluorescence-activated cell sorting (FACS) remains the gold standard technique for isolation of cells for many biomedical applications, like stem cell therapy. Here, we present a comprehensive and comparative account of some of the probes that are useful in FACS. Further, we illustrate how these techniques could be applied in biomedical research. It is postulated that intracellular molecular markers like nucleostemin (GNL3), alkaline phosphatase (ALPL) and HIRA can be used for improving the outcome of cardiac as well as bone regeneration. Another field that could utilize intracellular markers is diagnostics, and we propose the use of specific peptide nucleic acid probes (PNPs) against certain miRNAs for cancer surgical margin prediction. The newer techniques for single cell biology, based on intracellular molecules, will immensely enhance the repertoire of possible markers for the isolation of cell types useful in biomedical research.

  7. Computational Assessment of Pharmacokinetics and Biological Effects of Some Anabolic and Androgen Steroids.

    Science.gov (United States)

    Roman, Marin; Roman, Diana Larisa; Ostafe, Vasile; Ciorsac, Alecu; Isvoran, Adriana

    2018-02-05

    The aim of this study is to use computational approaches to predict the ADME-Tox profiles, pharmacokinetics, molecular targets, biological activity spectra and side/toxic effects of 31 anabolic and androgen steroids in humans. The following computational tools are used: (i) FAFDrugs4, SwissADME and admetSARfor obtaining the ADME-Tox profiles and for predicting pharmacokinetics;(ii) SwissTargetPrediction and PASS online for predicting the molecular targets and biological activities; (iii) PASS online, Toxtree, admetSAR and Endocrine Disruptomefor envisaging the specific toxicities; (iv) SwissDock to assess the interactions of investigated steroids with cytochromes involved in drugs metabolism. Investigated steroids usually reveal a high gastrointestinal absorption and a good oral bioavailability, may inhibit someof the human cytochromes involved in the metabolism of xenobiotics (CYP2C9 being the most affected) and reflect a good capacity for skin penetration. There are predicted numerous side effects of investigated steroids in humans: genotoxic carcinogenicity, hepatotoxicity, cardiovascular, hematotoxic and genitourinary effects, dermal irritations, endocrine disruption and reproductive dysfunction. These results are important to be known as an occupational exposure to anabolic and androgenic steroids at workplaces may occur and because there also is a deliberate human exposure to steroids for their performance enhancement and anti-aging properties.

  8. Computer graphic displays for microscopists assisting in evaluating radiation-damaged cells

    International Nuclear Information System (INIS)

    Bartels, P.H.; Olson, G.B.

    1984-01-01

    Computer analysis of digitized images of cells and tissues has developed into a highly refined methodology. In particular, the nuclear chromatin has numerous features that allow reliable recognition and classification of cells. This was hardly a surprise to cytopathologists, since chromatin texture and staining properties have always provided valuable clues for visual diagnosis. However, two aspects of computer assessment came as a surprise. First, there was the consistency with which chromatin distribution patterns express the state of the cell, its differentiation, and the sensitivity with which a change in the cell's environment is reflected in the chromatin. Second, chromatin texture provides highly discriminating, objectively measurable features that are not perceived by human visual assessment. Numerous studies have shown that computer assessment is capable of making clear-cut discriminations in cases where human cytodiagnostic evaluation is not effective

  9. Downregulation of the expression of HDGF attenuates malignant biological behaviors of hilar cholangiocarcinoma cells.

    Science.gov (United States)

    Liu, Yanfeng; Sun, Jingxian; Yang, Guangyun; Liu, Zhaojian; Guo, Sen; Zhao, Rui; Xu, Kesen; Wu, Xiaopeng; Zhang, Zhaoyang

    2015-09-01

    Hepatoma-derived growth factor (HDGF) has been reported to be a potential predictive and prognostic marker for several types of cancer and important in malignant biological behaviors. However, its role in human hilar cholangiocarcinoma remains to be elucidated. Our previous study demonstrated that high expression levels of HDGF in hilar cholangiocarcinoma tissues correlates with tumor progression and patient outcome. The present study aimed to elucidate the detailed functions of the HDGF protein. This was performed by downregulating the protein expression of HDGF in the FRH0201 hilar cholangiocarcinoma cell line by RNA interference (RNAi) in vitro, and revealed that downregulation of the HDGF protein significantly inhibited the malignant biological behavior of the FRH0201 cells. In addition, further investigation revealed that downregulation of the protein expression of HDGF significantly decreased the secretion of vascular endothelial growth factor, which may be the mechanism partially responsible for the inhibition of malignant biological behaviors. These findings demonstrated that HDGF is important in promoting malignant biological behaviors, including proliferation, migration and invasion of hilar cholangiocarcinoma FRH0201 cells. Inhibition of the expression of HDGF downregulated the malignant biological behaviors, suggesting that downregulation of the protein expression of HDGF by RNAi may be a novel therapeutic approach to inhibit the progression of hilar cholangiocarcinoma.

  10. A computational systems biology software platform for multiscale modeling and simulation: Integrating whole-body physiology, disease biology, and molecular reaction networks

    Directory of Open Access Journals (Sweden)

    Thomas eEissing

    2011-02-01

    Full Text Available Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multi-scale by nature, project work and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim® and MoBi® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug-drug or drug-metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach.

  11. An interactive computer lab of the galvanic cell for students in biochemistry.

    Science.gov (United States)

    Ahlstrand, Emma; Buetti-Dinh, Antoine; Friedman, Ran

    2018-01-01

    We describe an interactive module that can be used to teach basic concepts in electrochemistry and thermodynamics to first year natural science students. The module is used together with an experimental laboratory and improves the students' understanding of thermodynamic quantities such as Δ r G, Δ r H, and Δ r S that are calculated but not directly measured in the lab. We also discuss how new technologies can substitute some parts of experimental chemistry courses, and improve accessibility to course material. Cloud computing platforms such as CoCalc facilitate the distribution of computer codes and allow students to access and apply interactive course tools beyond the course's scope. Despite some limitations imposed by cloud computing, the students appreciated the approach and the enhanced opportunities to discuss study questions with their classmates and instructor as facilitated by the interactive tools. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(1):58-65, 2018. © 2017 The International Union of Biochemistry and Molecular Biology.

  12. Modelling effective dielectric properties of materials containing diverse types of biological cells

    International Nuclear Information System (INIS)

    Huclova, Sonja; Froehlich, Juerg; Erni, Daniel

    2010-01-01

    An efficient and versatile numerical method for the generation of different realistically shaped biological cells is developed. This framework is used to calculate the dielectric spectra of materials containing specific types of biological cells. For the generation of the numerical models of the cells a flexible parametrization method based on the so-called superformula is applied including the option of obtaining non-axisymmetric shapes such as box-shaped cells and even shapes corresponding to echinocytes. The dielectric spectra of effective media containing various cell morphologies are calculated focusing on the dependence of the spectral features on the cell shape. The numerical method is validated by comparing a model of spherical inclusions at a low volume fraction with the analytical solution obtained by the Maxwell-Garnett mixing formula, resulting in good agreement. Our simulation data for different cell shapes suggest that around 1MHz the effective dielectric properties of different cell shapes at different volume fractions significantly deviate from the spherical case. The most pronounced change exhibits ε eff between 0.1 and 1 MHz with a deviation of up to 35% for a box-shaped cell and 15% for an echinocyte compared with the sphere at a volume fraction of 0.4. This hampers the unique interpretation of changes in cellular features measured by dielectric spectroscopy when simplified material models are used.

  13. Precision control of recombinant gene transcription for CHO cell synthetic biology.

    Science.gov (United States)

    Brown, Adam J; James, David C

    2016-01-01

    The next generation of mammalian cell factories for biopharmaceutical production will be genetically engineered to possess both generic and product-specific manufacturing capabilities that may not exist naturally. Introduction of entirely new combinations of synthetic functions (e.g. novel metabolic or stress-response pathways), and retro-engineering of existing functional cell modules will drive disruptive change in cellular manufacturing performance. However, before we can apply the core concepts underpinning synthetic biology (design, build, test) to CHO cell engineering we must first develop practical and robust enabling technologies. Fundamentally, we will require the ability to precisely control the relative stoichiometry of numerous functional components we simultaneously introduce into the host cell factory. In this review we discuss how this can be achieved by design of engineered promoters that enable concerted control of recombinant gene transcription. We describe the specific mechanisms of transcriptional regulation that affect promoter function during bioproduction processes, and detail the highly-specific promoter design criteria that are required in the context of CHO cell engineering. The relative applicability of diverse promoter development strategies are discussed, including re-engineering of natural sequences, design of synthetic transcription factor-based systems, and construction of synthetic promoters. This review highlights the potential of promoter engineering to achieve precision transcriptional control for CHO cell synthetic biology. Copyright © 2015. Published by Elsevier Inc.

  14. Radiosensitivity of cancer-initiating cells and normal stem cells (or what the Heisenberg uncertainly principle has to do with biology).

    Science.gov (United States)

    Woodward, Wendy Ann; Bristow, Robert Glen

    2009-04-01

    Mounting evidence suggests that parallels between normal stem cell biology and cancer biology may provide new targets for cancer therapy. Prospective identification and isolation of cancer-initiating cells from solid tumors has promoted the descriptive and functional identification of these cells allowing for characterization of their response to contemporary cancer therapies, including chemotherapy and radiation. In clinical radiation therapy, the failure to clinically eradicate all tumor cells (eg, a lack of response, partial response, or nonpermanent complete response by imaging) is considered a treatment failure. As such, biologists have explored the characteristics of the small population of clonogenic cancer cells that can survive and are capable of repopulating the tumor after subcurative therapy. Herein, we discuss the convergence of these clonogenic studies with contemporary radiosensitivity studies that use cell surface markers to identify cancer-initiating cells. Implications for and uncertainties regarding incorporation of these concepts into the practice of modern radiation oncology are discussed.

  15. Symposium on single cell analysis and genomic approaches, Experimental Biology 2017 Chicago, Illinois, April 23, 2017.

    Science.gov (United States)

    Coller, Hilary A

    2017-09-01

    Emerging technologies for the analysis of genome-wide information in single cells have the potential to transform many fields of biology, including our understanding of cell states, the response of cells to external stimuli, mosaicism, and intratumor heterogeneity. At Experimental Biology 2017 in Chicago, Physiological Genomics hosted a symposium in which five leaders in the field of single cell genomics presented their recent research. The speakers discussed emerging methodologies in single cell analysis and critical issues for the analysis of single cell data. Also discussed were applications of single cell genomics to understanding the different types of cells within an organism or tissue and the basis for cell-to-cell variability in response to stimuli. Copyright © 2017 the American Physiological Society.

  16. Perturbation Biology: Inferring Signaling Networks in Cellular Systems

    Science.gov (United States)

    Miller, Martin L.; Gauthier, Nicholas P.; Jing, Xiaohong; Kaushik, Poorvi; He, Qin; Mills, Gordon; Solit, David B.; Pratilas, Christine A.; Weigt, Martin; Braunstein, Alfredo; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

    2013-01-01

    We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology. PMID:24367245

  17. Computational Medicine

    DEFF Research Database (Denmark)

    Nygaard, Jens Vinge

    2017-01-01

    The Health Technology Program at Aarhus University applies computational biology to investigate the heterogeneity of tumours......The Health Technology Program at Aarhus University applies computational biology to investigate the heterogeneity of tumours...

  18. Theories and models on the biological of cells in space

    Science.gov (United States)

    Todd, P.; Klaus, D. M.

    1996-01-01

    A wide variety of observations on cells in space, admittedly made under constraining and unnatural conditions in may cases, have led to experimental results that were surprising or unexpected. Reproducibility, freedom from artifacts, and plausibility must be considered in all cases, even when results are not surprising. The papers in symposium on 'Theories and Models on the Biology of Cells in Space' are dedicated to the subject of the plausibility of cellular responses to gravity -- inertial accelerations between 0 and 9.8 m/sq s and higher. The mechanical phenomena inside the cell, the gravitactic locomotion of single eukaryotic and prokaryotic cells, and the effects of inertial unloading on cellular physiology are addressed in theoretical and experimental studies.

  19. Assessment of environmental insults on lymphoid cells as detected by computer assisted morphometric techniques

    International Nuclear Information System (INIS)

    Olson, G.B.; Bartels, P.H.

    1984-01-01

    Ability to detect and monitor specific environmental insults with great sensitivity prompted the following study - the use of splenocytes and PBL as indicator cells to detect, monitor and differentiate between physically, chemically and biologically induced environmental insults. To be tested in this study is the hypothesis that different types of chemical, physical and biologic insults cause distinctive changes in the nuclear chromatin of the exposed cells. Should this assumption be warranted, one could monitor water, soil, air and food samples for undesirable chemicals and biological vectors (viruses), monitor people living near nuclear energy sites and people in radiation-related professions, and monitor cell samples obtained from people exposed to viral injections

  20. Cytotoxic Effect on Cancerous Cell Lines by Biologically Synthesized Silver Nanoparticles

    Directory of Open Access Journals (Sweden)

    Balaji Kulandaivelu

    Full Text Available The biosynthesis of nanoparticles has been proposed as an environmental friendly and cost effective alternative to chemical and physical methods. Silver nanoparticles are biologically synthesized and characterized were used in the study. The invitro cytotoxic effect of biologically synthesized silver nanoparticles against MCF-7 cancer cell lines were assessed. The cytotoxic effects of the silver nanoparticles could significantly inhibited MCF-7 cancer cell lines proliferation in a time and concentration-dependent manner by MTT assay. Acridine orange, ethidium bromide (AO/EB dual staining, caspase-3 and DNA fragmentation assays were carried out using various concentrations of silver nanoparticles ranging from 1 to 100 μg/mL. At 100 μg/mL concentration, the silver nanoparticles exhibited significant cytotoxic effects and the apoptotic features were confirmed through caspase-3 activation and DNA fragmentation assays. Western blot analysis has revealed that nanoparticle was able to induce cytochrome c release from the mitochondria, which was initiated by the inhibition of Bcl-2 and activation of Bax. Thus, the results of the present study indicate that biologically synthesized silver nanoparticles might be used to treat breast cancer. The present studies suggest that these nanoparticles could be a new potential adjuvant chemotherapeutic and chemo preventive agent against cytotoxic cells. However, it necessitates clinical studies to ascertain their potential as anticancer agents.

  1. Prospects and challenges of quantitative phase imaging in tumor cell biology

    Science.gov (United States)

    Kemper, Björn; Götte, Martin; Greve, Burkhard; Ketelhut, Steffi

    2016-03-01

    Quantitative phase imaging (QPI) techniques provide high resolution label-free quantitative live cell imaging. Here, prospects and challenges of QPI in tumor cell biology are presented, using the example of digital holographic microscopy (DHM). It is shown that the evaluation of quantitative DHM phase images allows the retrieval of different parameter sets for quantification of cellular motion changes in migration and motility assays that are caused by genetic modifications. Furthermore, we demonstrate simultaneously label-free imaging of cell growth and morphology properties.

  2. SU-G-TeP3-07: On the Development of Mechano-Biological Assessment of Leukemia Cells Using Optical Tweezers

    Energy Technology Data Exchange (ETDEWEB)

    Brost, E; Brooks, J; Piepenburg, J; Watanabe, Y; Hui, S [Therapeutic Radiology and Masonic Cancer Center, University of Minnesota, Minneapolis, MN (United States); Chakraborty, S; Das, T [Max Planck Institute for Intelligent Systems Department of New Materials and Biosystems Department of Mechanical Engineering, Indian Institute of Technology, Kharagpur (India); Green, A [Department of Physics, University of Saint Thomas, Saint Paul, MN (United States)

    2016-06-15

    Purpose: Patients with BCR-ABL (Ph +ve) acute lymphoblastic leukemia are at very high risk of relapse and mortality. In line with the NIH mission to understand the physical and biological processes, we seek to report mechano-biological method to assessment and distinguish treated/untreated leukemia cells. Methods: BCR-ABL leukemia cell populations and silica microspheres were trapped in a 100x magnification optical trapping system (λ=660 nm, 70 mW). Light refracted through the trapped sample was collected in the back focal plane by a quadrant detector to measure the positions of individual cells. The sample was driven at a known frequency and amplitude with a flexure translation stage, and the target’s response was recorded. The measured response was calibrated using the known driving parameters, and information about cell movements due to mechano-biological effects was extracted. Two leukemia cell populations were tested: a control group and a group treated with 2 Gy. Results: The mechano-biological movements of 10 microspheres, control cells, and treated cells were tracked over a ∼30 minute window at 1 minute intervals. The microsphere population did not see significant change in mechano-biological movements over the testing interval and remained constant. The control cell population saw a two-fold rise in activity that peaked around 1200 seconds, then dropped off sharply. The treated cell population saw a two-fold rise in activity that peaked at 400 seconds, and dropped off slowly. Conclusion: The investigated technique allows for direct measurement the movements of a trapped object due to mechano-biological effects such as thermal and extracellular motion. When testing microspheres, the mechano-biological activity remained constant over time due to the lack of biological factors. In both the control and treated cell populations, the mechano-biological activity was increased, possibly due to mitochondrial activation. This extra activity decreased over time

  3. The Use of Hebbian Cell Assemblies for Nonlinear Computation

    DEFF Research Database (Denmark)

    Tetzlaff, Christian; Dasgupta, Sakyasingha; Kulvicius, Tomas

    2015-01-01

    When learning a complex task our nervous system self-organizes large groups of neurons into coherent dynamic activity patterns. During this, a network with multiple, simultaneously active, and computationally powerful cell assemblies is created. How such ordered structures are formed while preser...... computing complex non-linear transforms and - for execution - must cooperate with each other without interference. This mechanism, thus, permits the self-organization of computationally powerful sub-structures in dynamic networks for behavior control....

  4. Nanobodies and recombinant binders in cell biology.

    Science.gov (United States)

    Helma, Jonas; Cardoso, M Cristina; Muyldermans, Serge; Leonhardt, Heinrich

    2015-06-08

    Antibodies are key reagents to investigate cellular processes. The development of recombinant antibodies and binders derived from natural protein scaffolds has expanded traditional applications, such as immunofluorescence, binding arrays, and immunoprecipitation. In addition, their small size and high stability in ectopic environments have enabled their use in all areas of cell research, including structural biology, advanced microscopy, and intracellular expression. Understanding these novel reagents as genetic modules that can be integrated into cellular pathways opens up a broad experimental spectrum to monitor and manipulate cellular processes. © 2015 Helma et al.

  5. Nanobodies and recombinant binders in cell biology

    Science.gov (United States)

    Helma, Jonas; Cardoso, M. Cristina; Muyldermans, Serge

    2015-01-01

    Antibodies are key reagents to investigate cellular processes. The development of recombinant antibodies and binders derived from natural protein scaffolds has expanded traditional applications, such as immunofluorescence, binding arrays, and immunoprecipitation. In addition, their small size and high stability in ectopic environments have enabled their use in all areas of cell research, including structural biology, advanced microscopy, and intracellular expression. Understanding these novel reagents as genetic modules that can be integrated into cellular pathways opens up a broad experimental spectrum to monitor and manipulate cellular processes. PMID:26056137

  6. Gradient matching methods for computational inference in mechanistic models for systems biology: a review and comparative analysis

    Directory of Open Access Journals (Sweden)

    Benn eMacdonald

    2015-11-01

    Full Text Available Parameter inference in mathematical models of biological pathways, expressed as coupled ordinary differential equations (ODEs, is a challenging problem in contemporary systems biology. Conventional methods involve repeatedly solving the ODEs by numerical integration, which is computationally onerous and does not scale up to complex systems. Aimed at reducing the computational costs, new concepts based on gradient matching have recently been proposed in the computational statistics and machine learning literature. In a preliminary smoothing step, the time series data are interpolated; then, in a second step, the parameters of the ODEs are optimised so as to minimise some metric measuring the difference between the slopes of the tangents to the interpolants, and the time derivatives from the ODEs. In this way, the ODEs never have to be solved explicitly. This review provides a concise methodological overview of the current state-of-the-art methods for gradient matching in ODEs, followed by an empirical comparative evaluation based on a set of widely used and representative benchmark data.

  7. Accumulation and biological effects of gallium in malignant cell lines in vitro

    International Nuclear Information System (INIS)

    Awano, Takayuki; Matsuzawa, Taiju

    1977-01-01

    Accumulation and biological effects of gallium (Ga) in malignant cells in vitro were studied. Biological effects were investigated cytokinetically and morphologically. The malignant cultured FM3A cells (originated from mammary carcinoma of C3H mice) accumulated 67 Ga actively. This accumulation was more intensive in proliferating cells than in non-proliferating cells. 6.5 percent of 67 Ga accumulated in the cultured FM3A cells was bound loosely at the cell surface. The colony forming capacity of C2W cells (originated from amelanotic melanoma of C57 Black mice ) was studied. The capacity decreased markedly when stable Ga was added to the medium in low concentration, but it decreased very little more in the range of rather high concentration. The growth response of FM3A cells to various concentrations of stable Ga was studied. The saturation density decreased and the doubling time became prolonged with increased Ga concentration. When 0.5 mM of stable Ga was added to the medium, the speed of proliferation changed markedly. The doubling time increased 1.7 times as compared to that before addition of Ga. The shape of the FM3A cells was usually spheroid in the medium. Swelling of the cells was observed when stable Ga was added to the culture medium. In particular, several per cent of these cells showed remarkable changes; that is, the cells were flattened and adhered to the dish and showed remarkable locomotion. It may be that these results are related to cell differentiation rather than to the cytotoxicity of stable Ga. (auth.)

  8. Accumulation and biological effects of gallium in malignant cell lines in vitro

    Energy Technology Data Exchange (ETDEWEB)

    Awano, T; Matsuzawa, T [Tohoku Univ., Sendai (Japan). Research Inst. for Tuberculosis, Leprosy and Cancer

    1977-02-01

    Accumulation and biological effects of gallium (Ga) in malignant cells in vitro were studied. Biological effects were investigated cytokinetically and morphologically. The malignant cultured FM3A cells (originated from mammary carcinoma of C3H mice) accumulated /sup 67/Ga actively. This accumulation was more intensive in proliferating cells than in non-proliferating cells. 6.5 percent of /sup 67/Ga accumulated in the cultured FM3A cells was bound loosely at the cell surface. The colony forming capacity of C2W cells (originated from amelanotic melanoma of C57 Black mice ) was studied. The capacity decreased markedly when stable Ga was added to the medium in low concentration, but it decreased very little more in the range of rather high concentration. The growth response of FM3A cells to various concentrations of stable Ga was studied. The saturation density decreased and the doubling time became prolonged with increased Ga concentration. When 0.5 mM of stable Ga was added to the medium, the speed of proliferation changed markedly. The doubling time increased 1.7 times as compared to that before addition of Ga. The shape of the FM3A cells was usually spheroid in the medium. Swelling of the cells was observed when stable Ga was added to the culture medium. In particular, several per cent of these cells showed remarkable changes; that is, the cells were flattened and adhered to the dish and showed remarkable locomotion. It may be that these results are related to cell differentiation rather than to the cytotoxicity of stable Ga.

  9. Natural Killer T Cells: An Ecological Evolutionary Developmental Biology Perspective.

    Science.gov (United States)

    Kumar, Amrendra; Suryadevara, Naveenchandra; Hill, Timothy M; Bezbradica, Jelena S; Van Kaer, Luc; Joyce, Sebastian

    2017-01-01

    Type I natural killer T (NKT) cells are innate-like T lymphocytes that recognize glycolipid antigens presented by the MHC class I-like protein CD1d. Agonistic activation of NKT cells leads to rapid pro-inflammatory and immune modulatory cytokine and chemokine responses. This property of NKT cells, in conjunction with their interactions with antigen-presenting cells, controls downstream innate and adaptive immune responses against cancers and infectious diseases, as well as in several inflammatory disorders. NKT cell properties are acquired during development in the thymus and by interactions with the host microbial consortium in the gut, the nature of which can be influenced by NKT cells. This latter property, together with the role of the host microbiota in cancer therapy, necessitates a new perspective. Hence, this review provides an initial approach to understanding NKT cells from an ecological evolutionary developmental biology (eco-evo-devo) perspective.

  10. Natural Killer T Cells: An Ecological Evolutionary Developmental Biology Perspective

    Science.gov (United States)

    Kumar, Amrendra; Suryadevara, Naveenchandra; Hill, Timothy M.; Bezbradica, Jelena S.; Van Kaer, Luc; Joyce, Sebastian

    2017-01-01

    Type I natural killer T (NKT) cells are innate-like T lymphocytes that recognize glycolipid antigens presented by the MHC class I-like protein CD1d. Agonistic activation of NKT cells leads to rapid pro-inflammatory and immune modulatory cytokine and chemokine responses. This property of NKT cells, in conjunction with their interactions with antigen-presenting cells, controls downstream innate and adaptive immune responses against cancers and infectious diseases, as well as in several inflammatory disorders. NKT cell properties are acquired during development in the thymus and by interactions with the host microbial consortium in the gut, the nature of which can be influenced by NKT cells. This latter property, together with the role of the host microbiota in cancer therapy, necessitates a new perspective. Hence, this review provides an initial approach to understanding NKT cells from an ecological evolutionary developmental biology (eco-evo-devo) perspective. PMID:29312339

  11. Natural Killer T Cells: An Ecological Evolutionary Developmental Biology Perspective

    Directory of Open Access Journals (Sweden)

    Amrendra Kumar

    2017-12-01

    Full Text Available Type I natural killer T (NKT cells are innate-like T lymphocytes that recognize glycolipid antigens presented by the MHC class I-like protein CD1d. Agonistic activation of NKT cells leads to rapid pro-inflammatory and immune modulatory cytokine and chemokine responses. This property of NKT cells, in conjunction with their interactions with antigen-presenting cells, controls downstream innate and adaptive immune responses against cancers and infectious diseases, as well as in several inflammatory disorders. NKT cell properties are acquired during development in the thymus and by interactions with the host microbial consortium in the gut, the nature of which can be influenced by NKT cells. This latter property, together with the role of the host microbiota in cancer therapy, necessitates a new perspective. Hence, this review provides an initial approach to understanding NKT cells from an ecological evolutionary developmental biology (eco-evo-devo perspective.

  12. Computation: A New Open Access Journal of Computational Chemistry, Computational Biology and Computational Engineering

    Directory of Open Access Journals (Sweden)

    Karlheinz Schwarz

    2013-09-01

    Full Text Available Computation (ISSN 2079-3197; http://www.mdpi.com/journal/computation is an international scientific open access journal focusing on fundamental work in the field of computational science and engineering. Computational science has become essential in many research areas by contributing to solving complex problems in fundamental science all the way to engineering. The very broad range of application domains suggests structuring this journal into three sections, which are briefly characterized below. In each section a further focusing will be provided by occasionally organizing special issues on topics of high interests, collecting papers on fundamental work in the field. More applied papers should be submitted to their corresponding specialist journals. To help us achieve our goal with this journal, we have an excellent editorial board to advise us on the exciting current and future trends in computation from methodology to application. We very much look forward to hearing all about the research going on across the world. [...

  13. Nano-ranged low-energy ion-beam-induced DNA transfer in biological cells

    Energy Technology Data Exchange (ETDEWEB)

    Yu, L.D., E-mail: yuld@fnrf.science.cmu.ac.th [Thailand Center of Excellence in Physics, Commission on Higher Education, 328 Si Ayutthaya Road, Bangkok 10400 (Thailand); Plasma and Beam Physics Research Facility, Department of Physics and Materials Science, Faculty of Science, Chiang Mai University, Chiang Mai 50200 (Thailand); Wongkham, W. [Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200 (Thailand); Prakrajang, K. [Plasma and Beam Physics Research Facility, Department of Physics and Materials Science, Faculty of Science, Chiang Mai University, Chiang Mai 50200 (Thailand); Sangwijit, K.; Inthanon, K. [Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200 (Thailand); Thongkumkoon, P. [Thailand Center of Excellence in Physics, Commission on Higher Education, 328 Si Ayutthaya Road, Bangkok 10400 (Thailand); Plasma and Beam Physics Research Facility, Department of Physics and Materials Science, Faculty of Science, Chiang Mai University, Chiang Mai 50200 (Thailand); Wanichapichart, P. [Thailand Center of Excellence in Physics, Commission on Higher Education, 328 Si Ayutthaya Road, Bangkok 10400 (Thailand); Membrane Science and Technology Research Center, Department of Physics, Faculty of Science, Prince of Songkla University, Hat Yai, Songkla 90112 (Thailand); Anuntalabhochai, S. [Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200 (Thailand)

    2013-06-15

    Low-energy ion beams at a few tens of keV were demonstrated to be able to induce exogenous macromolecules to transfer into plant and bacterial cells. In the process, the ion beam with well controlled energy and fluence bombarded living cells to cause certain degree damage in the cell envelope in nanoscales to facilitate the macromolecules such as DNA to pass through the cell envelope and enter the cell. Consequently, the technique was applied for manipulating positive improvements in the biological species. This physical DNA transfer method was highly efficient and had less risk of side-effects compared with chemical and biological methods. For better understanding of mechanisms involved in the process, a systematic study on the mechanisms was carried out. Applications of the technique were also expanded from DNA transfer in plant and bacterial cells to DNA transfection in human cancer cells potentially for the stem cell therapy purpose. Low-energy nitrogen and argon ion beams that were applied in our experiments had ranges of 100 nm or less in the cell envelope membrane which was majorly composed of polymeric cellulose. The ion beam bombardment caused chain-scission dominant damage in the polymer and electrical property changes such as increase in the impedance in the envelope membrane. These nano-modifications of the cell envelope eventually enhanced the permeability of the envelope membrane to favor the DNA transfer. The paper reports details of our research in this direction.

  14. Nano-ranged low-energy ion-beam-induced DNA transfer in biological cells

    International Nuclear Information System (INIS)

    Yu, L.D.; Wongkham, W.; Prakrajang, K.; Sangwijit, K.; Inthanon, K.; Thongkumkoon, P.; Wanichapichart, P.; Anuntalabhochai, S.

    2013-01-01

    Low-energy ion beams at a few tens of keV were demonstrated to be able to induce exogenous macromolecules to transfer into plant and bacterial cells. In the process, the ion beam with well controlled energy and fluence bombarded living cells to cause certain degree damage in the cell envelope in nanoscales to facilitate the macromolecules such as DNA to pass through the cell envelope and enter the cell. Consequently, the technique was applied for manipulating positive improvements in the biological species. This physical DNA transfer method was highly efficient and had less risk of side-effects compared with chemical and biological methods. For better understanding of mechanisms involved in the process, a systematic study on the mechanisms was carried out. Applications of the technique were also expanded from DNA transfer in plant and bacterial cells to DNA transfection in human cancer cells potentially for the stem cell therapy purpose. Low-energy nitrogen and argon ion beams that were applied in our experiments had ranges of 100 nm or less in the cell envelope membrane which was majorly composed of polymeric cellulose. The ion beam bombardment caused chain-scission dominant damage in the polymer and electrical property changes such as increase in the impedance in the envelope membrane. These nano-modifications of the cell envelope eventually enhanced the permeability of the envelope membrane to favor the DNA transfer. The paper reports details of our research in this direction.

  15. Discrepancy of biologic behavior influenced by bone marrow derived cells in lung cancer.

    Science.gov (United States)

    Zhang, Jie; Niu, Xiao-Min; Liao, Mei-Lin; Liu, Yun; Sha, Hui-Fang; Zhao, Yi; Yu, Yong-Feng; Tan, Qiang; Xiang, Jia-Qing; Fang, Jing; Lv, Dan-Dan; Li, Xue-Bing; Lu, Shun; Chen, Hai-Quan

    2010-11-01

    Disseminated cancer cells may initially require local nutrients and growth factors to thrive and survive in bone marrow. However, data on the influence of bone marrow derived cells (BMDC, also called bone stromal cells in some publications) on lung cancer cells is largely unexplored. This study explored the mechanism of how bone stromal factors contribute to the bone tropism in lung cancer. The difference among lung cancer cell lines in their abilities to metastasize to bone was found using the SCID animal model. Supernatant of bone marrow aspiration (BM) and condition medium from human bone stromal cells (BSC) were used to study the activity of bone stromal factors. We found bone stromal factors significantly increased the proliferation, invasion, adhesion and expression of angiogenosis-related factors, and inhibited the apoptosis for high bone metastasis H460 lung cancer cells. These biologic effects were not seen in SPC-A1 or A549 cells, which are low bone metastasis lung cancer cells. Adhesion of H460 cells to surface coated with bone stromal cells can activate some signal transduction pathways, and alter the expression of adhesion associated factors, including integrin β 3 and ADAMTS-1, two potential targets related with bone metastasis. We concluded that bone marrow derived cells had a profound effect on biological behavior of lung cancers, therefore favoring the growth of lung cancer cells in bone.

  16. Experimental and Computational Characterization of Biological Liquid Crystals: A Review of Single-Molecule Bioassays

    Directory of Open Access Journals (Sweden)

    Sungsoo Na

    2009-09-01

    Full Text Available Quantitative understanding of the mechanical behavior of biological liquid crystals such as proteins is essential for gaining insight into their biological functions, since some proteins perform notable mechanical functions. Recently, single-molecule experiments have allowed not only the quantitative characterization of the mechanical behavior of proteins such as protein unfolding mechanics, but also the exploration of the free energy landscape for protein folding. In this work, we have reviewed the current state-of-art in single-molecule bioassays that enable quantitative studies on protein unfolding mechanics and/or various molecular interactions. Specifically, single-molecule pulling experiments based on atomic force microscopy (AFM have been overviewed. In addition, the computational simulations on single-molecule pulling experiments have been reviewed. We have also reviewed the AFM cantilever-based bioassay that provides insight into various molecular interactions. Our review highlights the AFM-based single-molecule bioassay for quantitative characterization of biological liquid crystals such as proteins.

  17. Engineering Therapeutic T Cells: From Synthetic Biology to Clinical Trials.

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    Esensten, Jonathan H; Bluestone, Jeffrey A; Lim, Wendell A

    2017-01-24

    Engineered T cells are currently in clinical trials to treat patients with cancer, solid organ transplants, and autoimmune diseases. However, the field is still in its infancy. The design, and manufacturing, of T cell therapies is not standardized and is performed mostly in academic settings by competing groups. Reliable methods to define dose and pharmacokinetics of T cell therapies need to be developed. As of mid-2016, there are no US Food and Drug Administration (FDA)-approved T cell therapeutics on the market, and FDA regulations are only slowly adapting to the new technologies. Further development of engineered T cell therapies requires advances in immunology, synthetic biology, manufacturing processes, and government regulation. In this review, we outline some of these challenges and discuss the contributions that pathologists can make to this emerging field.

  18. Single cell adhesion assay using computer controlled micropipette.

    Directory of Open Access Journals (Sweden)

    Rita Salánki

    Full Text Available Cell adhesion is a fundamental phenomenon vital for all multicellular organisms. Recognition of and adhesion to specific macromolecules is a crucial task of leukocytes to initiate the immune response. To gain statistically reliable information of cell adhesion, large numbers of cells should be measured. However, direct measurement of the adhesion force of single cells is still challenging and today's techniques typically have an extremely low throughput (5-10 cells per day. Here, we introduce a computer controlled micropipette mounted onto a normal inverted microscope for probing single cell interactions with specific macromolecules. We calculated the estimated hydrodynamic lifting force acting on target cells by the numerical simulation of the flow at the micropipette tip. The adhesion force of surface attached cells could be accurately probed by repeating the pick-up process with increasing vacuum applied in the pipette positioned above the cell under investigation. Using the introduced methodology hundreds of cells adhered to specific macromolecules were measured one by one in a relatively short period of time (∼30 min. We blocked nonspecific cell adhesion by the protein non-adhesive PLL-g-PEG polymer. We found that human primary monocytes are less adherent to fibrinogen than their in vitro differentiated descendants: macrophages and dendritic cells, the latter producing the highest average adhesion force. Validation of the here introduced method was achieved by the hydrostatic step-pressure micropipette manipulation technique. Additionally the result was reinforced in standard microfluidic shear stress channels. Nevertheless, automated micropipette gave higher sensitivity and less side-effect than the shear stress channel. Using our technique, the probed single cells can be easily picked up and further investigated by other techniques; a definite advantage of the computer controlled micropipette. Our experiments revealed the existence of a

  19. 20170312 - Computer Simulation of Developmental ...

    Science.gov (United States)

    Rationale: Recent progress in systems toxicology and synthetic biology have paved the way to new thinking about in vitro/in silico modeling of developmental processes and toxicities, both for embryological and reproductive impacts. Novel in vitro platforms such as 3D organotypic culture models, engineered microscale tissues and complex microphysiological systems (MPS), together with computational models and computer simulation of tissue dynamics, lend themselves to a integrated testing strategies for predictive toxicology. As these emergent methodologies continue to evolve, they must be integrally tied to maternal/fetal physiology and toxicity of the developing individual across early lifestage transitions, from fertilization to birth, through puberty and beyond. Scope: This symposium will focus on how the novel technology platforms can help now and in the future, with in vitro/in silico modeling of complex biological systems for developmental and reproductive toxicity issues, and translating systems models into integrative testing strategies. The symposium is based on three main organizing principles: (1) that novel in vitro platforms with human cells configured in nascent tissue architectures with a native microphysiological environments yield mechanistic understanding of developmental and reproductive impacts of drug/chemical exposures; (2) that novel in silico platforms with high-throughput screening (HTS) data, biologically-inspired computational models of

  20. Beyond a pedagogical tool: 30 years of Molecular biology of the cell.

    Science.gov (United States)

    Serpente, Norberto

    2013-02-01

    In 1983, a bulky and profusely illustrated textbook on molecular and cell biology began to inhabit the shelves of university libraries worldwide. The effect of capturing the eyes and souls of biologists was immediate as the book provided them with a new and invigorating outlook on what cells are and what they do.

  1. Cell biology apps for Apple devices.

    Science.gov (United States)

    Stark, Louisa A

    2012-01-01

    Apps for touch-pad devices hold promise for guiding and supporting learning. Students may use them in the classroom or on their own for didactic instruction, just-in-time learning, or review. Since Apple touch-pad devices (i.e., iPad and iPhone) have a substantial share of the touch-pad device market (Campbell, 2012), this Feature will explore cell biology apps available from the App Store. My review includes iPad and iPhone apps available in June 2012, but does not include courses, lectures, podcasts, audiobooks, texts, or other books. I rated each app on a five-point scale (1 star = lowest; 5 stars = highest) for educational and production values; I also provide an overall score.

  2. G‐LoSA: An efficient computational tool for local structure‐centric biological studies and drug design

    Science.gov (United States)

    2016-01-01

    Abstract Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G‐LoSA. G‐LoSA aligns protein local structures in a sequence order independent way and provides a GA‐score, a chemical feature‐based and size‐independent structure similarity score. Our benchmark validation shows the robust performance of G‐LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure‐centric comparative biology studies. In particular, G‐LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G‐LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer‐aided drug design. We hope that G‐LoSA can be a useful computational method for exploring interesting biological problems through large‐scale comparison of protein local structures and facilitating drug discovery research and development. G‐LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. PMID:26813336

  3. Coalescent models for developmental biology and the spatio-temporal dynamics of growing tissues.

    Science.gov (United States)

    Smadbeck, Patrick; Stumpf, Michael P H

    2016-04-01

    Development is a process that needs to be tightly coordinated in both space and time. Cell tracking and lineage tracing have become important experimental techniques in developmental biology and allow us to map the fate of cells and their progeny. A generic feature of developing and homeostatic tissues that these analyses have revealed is that relatively few cells give rise to the bulk of the cells in a tissue; the lineages of most cells come to an end quickly. Computational and theoretical biologists/physicists have, in response, developed a range of modelling approaches, most notably agent-based modelling. These models seem to capture features observed in experiments, but can also become computationally expensive. Here, we develop complementary genealogical models of tissue development that trace the ancestry of cells in a tissue back to their most recent common ancestors. We show that with both bounded and unbounded growth simple, but universal scaling relationships allow us to connect coalescent theory with the fractal growth models extensively used in developmental biology. Using our genealogical perspective, it is possible to study bulk statistical properties of the processes that give rise to tissues of cells, without the need for large-scale simulations. © 2016 The Authors.

  4. Computational adaptive optics for broadband optical interferometric tomography of biological tissue.

    Science.gov (United States)

    Adie, Steven G; Graf, Benedikt W; Ahmad, Adeel; Carney, P Scott; Boppart, Stephen A

    2012-05-08

    Aberrations in optical microscopy reduce image resolution and contrast, and can limit imaging depth when focusing into biological samples. Static correction of aberrations may be achieved through appropriate lens design, but this approach does not offer the flexibility of simultaneously correcting aberrations for all imaging depths, nor the adaptability to correct for sample-specific aberrations for high-quality tomographic optical imaging. Incorporation of adaptive optics (AO) methods have demonstrated considerable improvement in optical image contrast and resolution in noninterferometric microscopy techniques, as well as in optical coherence tomography. Here we present a method to correct aberrations in a tomogram rather than the beam of a broadband optical interferometry system. Based on Fourier optics principles, we correct aberrations of a virtual pupil using Zernike polynomials. When used in conjunction with the computed imaging method interferometric synthetic aperture microscopy, this computational AO enables object reconstruction (within the single scattering limit) with ideal focal-plane resolution at all depths. Tomographic reconstructions of tissue phantoms containing subresolution titanium-dioxide particles and of ex vivo rat lung tissue demonstrate aberration correction in datasets acquired with a highly astigmatic illumination beam. These results also demonstrate that imaging with an aberrated astigmatic beam provides the advantage of a more uniform depth-dependent signal compared to imaging with a standard gaussian beam. With further work, computational AO could enable the replacement of complicated and expensive optical hardware components with algorithms implemented on a standard desktop computer, making high-resolution 3D interferometric tomography accessible to a wider group of users and nonspecialists.

  5. Modeling drug- and chemical- induced hepatotoxicity with systems biology approaches

    Directory of Open Access Journals (Sweden)

    Sudin eBhattacharya

    2012-12-01

    Full Text Available We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of ‘toxicity pathways’ is described in the context of the 2007 US National Academies of Science report, Toxicity testing in the 21st Century: A Vision and A Strategy. Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically-based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular virtual tissue model of the liver lobule that combines molecular circuits in individual hepatocytes with cell-cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the AhR toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsymTM to understand drug-induced liver injury (DILI, the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales.

  6. NK cell-based cancer immunotherapy: from basic biology to clinical application.

    Science.gov (United States)

    Li, Yang; Yin, Jie; Li, Ting; Huang, Shan; Yan, Han; Leavenworth, JianMei; Wang, Xi

    2015-12-01

    Natural killer (NK) cells, which recognize and kill target cells independent of antigen specificity and major histocompatibility complex (MHC) matching, play pivotal roles in immune defence against tumors. However, tumor cells often acquire the ability to escape NK cell-mediated immune surveillance. Thus, understanding mechanisms underlying regulation of NK cell phenotype and function within the tumor environment is instrumental for designing new approaches to improve the current cell-based immunotherapy. In this review, we elaborate the main biological features and molecular mechanisms of NK cel